Computational biology / bioinformatics Books
John Wiley and Sons Ltd Root Genomics and Soil Interactions
Book SynopsisFully integrated and comprehensive in its coverage, Root Genomics and Soil Interactions examines the use of genome-based technologies to understand root development and adaptability to biotic and abiotic stresses and changes in the soil environment.Table of ContentsContributors ix Preface xv Chapter 1 Genomics of Root Development 3Boris Parizot and Tom Beeckman Introduction 3 Genomics of LRI 7 Rise of New Technologies to Understand Lateral Root Development 19 ComparativOmics, the Future 20 Acknowledgments 21 References 21 Chapter 2 The Complex Eukaryotic Transcriptome: Nonprotein-Coding RNAs and Root Development 29F. Ariel, A.B. Moreno, F. Bardou, and M. Crespi Genomic Approaches Reveal Novel Aspects of the Eukaryotic Transcriptome 29 The Role of RNA-Binding Proteins in npcRNA Metabolism and Activity 34 Nonprotein-Coding RNAs in Root Development 38 Future Perspectives 42 Acknowledgments 42 References 42 Chapter 3 Genomics of Auxin Action in Roots 49Elisabeth L. Williams and Ive De Smet Introduction 49 The Basis of Auxin Biology 49 Auxin Genomics in Root Development 55 Auxin and Root Hair Development 56 Auxin in Gravitropism 57 Auxin in LR Initiation 57 Conclusion 58 Acknowledgments 58 References 58 Chapter 4 Cell-Type Resolution Analysis of Root Development and Environmental Responses 63Jose R. Dinneny Introduction 63 Tools for Cell-Type Resolution Analysis 64 Analysis of Spatiotemporal Expression Patterns in the Arabidopsis Root 69 Analysis of Cell-Type-Specific Expression Patterns in the Rice Root 70 Cell-Type-Specific Analysis of Auxin 71 Cell-Type-Specific Analyses of Chromatin 71 Cell-Type-Specific Analyses of Responses to Environmental Change 72 Future Prospects 76 Acknowledgments 76 References 77 Chapter 5 Toward a Virtual Root: Interaction of Genomics and Modeling to Develop Predictive Biology Approaches 79Julien Lavenus, Leah Band, Alistair Middleton, Michael Wilson, Mikael Lucas, Laurent Laplaze, and Malcolm Bennett Assembling Root Gene Regulatory Pathways Using Genomics 79 Modeling Well-Characterized Small Root Gene Regulatory Networks 81 Building New Large-Scale Root Gene Regulatory Network 84 Multi-Scale Modeling Approaches to Study Root Growth and Development 88 Conclusions and Future Challenges 89 References 91 Chapter 6 Genomics of Root Hairs 93Hyung-Taeg Cho Genomics with Single Cells 93 Root Hair Development 94 High-Throughput Approaches for the Characterization of Root Hairs 95 Functions of Root Hair-Specific Genes 103 The Regulatory Pathway for Root Hair-Specific Genes 110 Perspective 111 Acknowledgments 111 References 112 Chapter 7 The Effects of Moisture Extremes on Plant Roots and Their Connections with Other Abiotic Stresses 117Laura M. Vaughn and Henry T. Nguyen Introduction 117 Low Water Availability—Drought 118 Excess Water—Soil Waterlogging, Flooding, and Submergence 128 Common Plant Root Responses to Abiotic Stressors 135 Continuing Challenges in Breeding for Plant Root Systems Tolerant to Abiotic Stress 137 Acknowledgments 138 References 138 Chapter 8 Legume Roots and Nitrogen-Fixing Symbiotic Interactions 145Philippe Laporte, Andreas Niebel, and Florian Frugier Genetic Dissection of the Legume Root System 145 Functional Genomic Analyses of Legume Nodules and Roots 155 Concluding Remarks 161 Acknowledgments 162 References 162 Chapter 9 What the Genomics of Arbuscular Mycorrhizal Symbiosis Teaches Us about Root Development 171Damien Formey, Cyril Jourda, Christophe Roux, and Pierre-Marc Delaux Forward and Reverse Genetics for Identifying Myc Mutants 172 Comparative Transcriptomics of AM Symbiosis: Toward Identification of Genes Involved in Root Development 175 Small RNAs in AM Symbiosis 181 Acknowledgments 183 References 183 Chapter 10 How Pathogens Affect Root Structure 189Michael Quentin, Tarek Hewezi, Isabelle Damiani, Pierre Abad, Thomas Baum, and Bruno Favery Introduction 189 Root Infection and Feeding Cell Ontogenesis 190 Genome-Wide Analysis of the Plant Response to Infection 192 The Plant Cytoskeleton Is Targeted by Root Pathogens 193 Root Pathogens Hijack Cell Cycle Regulators 194 Severe Cell Wall Remodeling Is Associated with Feeding Site Formation 195 Phytohormones Regulating Development and Defense May Control Feeding Site Formation 196 Role of miRNAs in Feeding Site Formation and Function 198 Nematode Effectors That Alter Root Cell Development during Parasitism 200 Conclusion 203 Acknowledgments 204 References 204 Chapter 11 Genomics of the Root—Actinorhizal Symbiosis 211Valerie Hocher, Nicole Alloisio, Laurent Laplaze, Didier Bogusz, and Philippe Normand Introduction 211 Actinorhizal Symbiosis 212 Development of Actinorhizal Nodules 214 Genomic Resources for Studying Actinorhizal Symbiosis 217 What Did We Learn from Actinorhizal Genomics? 220 Conclusion and Future Directions 222 Acknowledgments 222 References 223 Chapter 12 Plant Growth Promoting Rhizobacteria and Root Architecture 227Thais L.G. Carvalho, Paulo C.G. Ferreira, and Adriana S. Hemerly Introduction 227 Different Root Niches for PGPR Colonization 228 PGPR Recognition by Plants 229 Modulation of Root Growth and Architecture by PGPRs 232 Mechanisms of Plant Growth Promotion by PGPRs 234 Plant Genetic Programs Controlling Modulation of Root Growth and Architecture by PGPRs 240 Conclusions 241 Acknowledgments 242 References 242 Chapter 13 Translational Root Genomics for Crop Improvement 249Reyazul Rouf Mir, Mahendar Thudi, Siva K. Chamarthi, L. Krishnamurthy, Pooran M. Gaur, and Rajeev K. Varshney Introduction 249 Molecular Dissection of Root Trait 258 Molecular Breeding for Root Traits 259 Summary and Outlook 260 Acknowledgments 260 References 260 Index 265
£171.86
John Wiley & Sons Inc InSitu PCR Techniques
Book SynopsisThis book describes comprehensive step-by-step protocols for the delineation of genetic amplification and histological detection techniques. Each procedure has been tested and validated for its sensitivity, precision, and reproducibility, and the authors give advice on the design of primers for PCR applications and on optimizing these protocols for use with plant, insect, and prokaryotic cells.Table of ContentsOverview; Review of the PCR Technique; Preliminary Solution-Based Reactions; Preparation of Glass Slides and Tissues; In Situ PCR: DNA and RNA Targets; Special Applications of In Situ Amplification; Hybridization Reactions; Validation and Controls; Materials and Methods; Select Biography; Appendices; Index; About the Authors.
£125.96
John Wiley & Sons Inc Applied Antisense Oligonucleotide Technology
Book SynopsisThis text aims to address the need for investigators to understand the basic concepts, as well as the practical concerns, associated with the use of antisense oligonucleotides in modifying gene expression.Trade Review"This book will be most useful to workers in the field and advanced graduate students." --The Quarterly Review of Biology, June 1999Table of ContentsCHEMISTRY, OLD AND NEW. Oligonucleoside Methylphosphonates: Synthesis and Properties (P. Miller). Oligo(Nucleoside Phosphorothioate)s (P. Guga, et al.). Modified Oligodeoxynucleotides as Antisense Therapeutics (P. Seeberger & M. Caruthers). Novel Chemistry (K. Altmann, et al.). OLIGONUCLEOTIDE INTERNALIZATION, MECHANISM OF ACTION, AND NON-SEQUENCE SPECIFICITY. Cellular Uptake and Biodistribution of Oligodeoxynucleotides (B. Hanss, et al.). Use of Cationic Lipid Complexes for Antisense Oligonucleotide Delivery (C. Bennett). Nonantisense Effects of Antisense Oligonucleotides (L. Neckers & K. Iyer). Ribonuclease H-Mediated Antisense Effects of Oligonucleotides and Controls for Antisense Experiments (D. Tidd). SEQUENCE-SPECIFIC INHIBITION OF GENE EXPRESSION. The Development of C-5 Propyne Oligonucleotides as Inhibitors of Gene Function (W. Flanagan & R. Wagner). The Use of Antisense Oligonucleotides to Inhibit Expression of Isozymes of Protein Kinase C (N. Dean, et al.). BCR-ABL as a Target for Antisense Intervention (S. O'Brien & T. Smetsers). The NF-kB Transcription Factor (R. Narayanan). Disruption of the Map Kinase Signaling Pathway Using Antisense Oligonucleotide Inhibitors Targeted to RAS and RAF Kinase (B. Monia). Protein Kinase A-Directed Antisense Blockade of Cancer Growth: Single Gene-Based Therapeutic Approach (Y. Cho-Chung). Use of Antisense Oligonucleotides in the Central Nervous System: Why Such Success? (M. McCarthy). APPLIED ANTISENSE OLIGONUCLEOTIDE THERAPEUTICS. Perturbing Hematopoietic Cell Gene Expression with Oligodeoxynucleotides: Research and Clinical Applications (A. Gewirtz & M. Ratajczak). BCL2 (B. Jansen & B. Brown). Biological Activity of Guanosine Quartet-Forming Oligonucleotides (R. Rando & M. Hogan). OLIGONUCLEOTIDES AS ANTI-HIV AGENTS. Perspectives on Antisense Technology Against HIV (J. Gee, et al.). In Vivo Pharmacokinetics of Oligonucleotides (S. Agrawal). Early Clinical Trails with Gem 91, A Systemic Oligodeoxynucleotide (R. Martin). THERAPEUTIC OLIGONUCLEOTIDE DATA BASE: PHARMACOKINETICS, IMMUNE STIMULATION, AND USE AS ANTIRESTENOTIC AGENTS. Antisense Therapy to Inhibit Angioplasty Restenosis (L. Rabbani & W. Wang). Pharmacokinetics of Oligonucleotides: A Review of Current Knowledge and Issues for the Future (T. Wallace & P. Cossum). Leukocyte Stimulation by Oligodeoxynucleotides (A. Krieg). SELECTED OLIGODEOXYNUCLEOTIDE DEVELOPMENTAL TOPICS: SPLICING AND TRIPLEXES. Modification of Alternative Splicing of Pre-mRNA by Antisense Oligonucleotides (R. Kole). Gene-Targeted Triple-Helix-Forming Oligonucleotides (F. Svinarchuk & C. Malvy). Triplex-Forming Oligonucleotides for Genetic Manipulation: An Alternative View (A. Faruqi & P. Glazer). A REVIEW OF RIBOZYME TECHNOLOGY. Therapeutic Ribozymes: Principles, Applications, and Problems (J. Rossi). Index.
£250.16
John Wiley & Sons Inc Handbook of Comparative Genomics Principles and
Book SynopsisThis book provides the basics by which researchers can approach basic and applied problems of management and enquiry of biosequence databases, as well as learn to develop computer models for the description of biological processes.Trade Review"…an excellent addition to the field of comparative genomics." (ASM News, December 2004) “...will provide interesting reading and perspective to almost everyone involved in biological sciences.” (Quarterly Review of Biology, March 2004) "...certainly deserves a place in institutional libraries...depth of material covered is right for the busy scientist...precise and detailed..." (Briefings in Functional Genomics & Proteomics, Vol 2(4), February 2004) "...this book gives an illuminating look at the study of genomes through their sequence..." (Human Genomics, January 2004) "...covers basic and applied problems in the emerging field of comparative functional genomics..." (Genetic Engineering News, Vol 23(14), 2003)Table of ContentsSECTION I: GENOME FEATURES. Preface. The Prokaryotic Genome. Eukaryotes. Organelles. SECTION II: METHODOLOGIES. Molecular Biology Techniques for Genomics. Biological Databases. Computatonal Methods for the Analysis of Genome Sequence Data. SECTION III: COMPARATIVE GENOMICS. Molecular Evolution. Molecular Phylogeny. Appendix I.
£152.06
John Wiley & Sons Inc Guide to Analysis of DNA Microarray Data
Book SynopsisWritten for biologists and medical researchers who don''t have any special training in data analysis and statistics, Guide to Analysis of DNA Microarray Data, Second Edition begins where DNA array equipment leaves off: the image produced by the microarray. The text deals with the questions that arise starting at this point, providing an introduction to microarray technology, then moving on to image analysis, data analysis, cluster analysis, and beyond. With all chapters rewritten, updated, and expanded to include the latest generation of technology and methods, Guide to Analysis of DNA Microarray Data, Second Edition offers practitioners reliable information using concrete examples and a clear, comprehensible style. This Second Edition features entirely new chapters on: * Image analysis * Experiment design * Automated analysis, integrated analysis, and systems biology * Interpretation of results Intended for readers seeking practical applications, thTrade Review"Bioinformaticians, statisticians, computer scientists, biologists, and medical researchers will find this well written book extremely useful." (Journal of Statistical Computation and Simulation, September 2005) "...useful for anybody who wants to catch up with the marvels of modern laboratory technology..." (Chemistry & Industry, 17th January 2005) "This book would be useful for anyone working with the DNA microarray technology." (Annals of Biomedical Engineering, November 2004) "...concisely written with clear illustrations and tables [with]...a good deal of new material." (E-STREAMS, November 2004)Table of ContentsPreface. Acknowledgments. 1. Introduction to DNA Microarray Technology. 1.1 Hybridization. 1.2 Gold Rush? 1.3 The Technology behind DNA Microarrays. 1.3.1 Affymetrix GeneChip Technology. 1.3.2 Spotted Arrays. 1.3.3 Digital Micromirror Arrays. 1.3.4 Inkjet Arrays. 1.3.5 Bead Arrays. 1.3.6 Serial Analysis of Gene Expression (SAGE). 1.4 Parallel Sequencing on Microbead Arrays. 1.4.1 Emerging Technologies 1.5 Example: Affymetrix vs. Spotted Arrays. 1.6 Summary. 1.7 Further Reading. 2. Overview of Data Analysis. 3. Image Analysis. 3.1 Gridding. 3.2 Segmentation. 3.3 Intensity Extraction. 3.4 Background Correction. 3.5 Software. 3.5.1 Free Software for Array Image Analysis. 3.5.2 Commercial Software for Array Image Analysis. 3.6 Summary. 3.7 Further Reading. 4. Basic Data Analysis. 4.1 Normalization. 4.1.1 One or More Genes are Assumed Expressed at Constant Rate. 4.1.2 Sum of Genes is Assumed Constant. 4.1.3 Subset of Genes is Assumed Constant. 4.1.4 Majority of Genes Assumed Constant. 4.1.5 Spike Controls. 4.2 Dye Bias, Spatial Bias, Print Tip Bias. 4.3 Expression Indices. 4.3.1 Average Difference. 4.3.2 Signal. 4.3.3 Model-Based Expression Index. 4.3.4 Robust Multiarray Average. 4.3.5 Position Dependent Nearest Neighbor Model. 4.4 Detection of Outliers. 4.5 Fold Change. 4.6 Significance. 4.6.1 Multiple Conditions. 4.6.2 Nonparametric Tests. 4.6.3 Correction for Multiple Testing. 4.6.4 Example I: t-Test and ANOVA. 4.6.5 Example II: Number of Replicates. 4.7 Mixed Cell Populations. 4.8 Summary. 4.9 Further Reading. 5. Visualization by Reduction of Dimensionality. 5.1 Principal Component Analysis. 5.2 Example 1: PCA on Small Data Matrix. 5.3 Example 2: PCA on Real Data. 5.4 Summary. 5.5 Further Reading. 6. Cluster Analysis. 6.1 Hierarchical Clustering. 6.2 K-means Clustering. 6.3 Self-Organizing Maps. 6.4 Distance Measures. 6.4.1 Example: Comparison of Distance Measures. 6.5 Gene Normalization. 6.6 Visualization of Clusters. 6.6.1 Example: Visualization of Gene Clusters in Bladder Cancer. 6.7 Summary. 6.8 Further Reading. 7. Beyond Cluster Analysis. 7.1 Function Prediction. 7.2 Discovery of Regulatory Elements in Promoter Regions. 7.2.1 Example 1: Discovery of Proteasomal Element. 7.2.2 Example 2: Rediscovery of Mlu Cell Cycle Box (MCB). 7.3 Summary. 7.4 Further Reading. 8. Automated Analysis, Integrated Analysis and Systems Biology. 8.1 Integrated Analysis. 8.2 Systems Biology. 8.3 Further Reading. 9. Reverse Engineering of Regulatory Networks. 9.1 The Time-Series Approach. 9.2 The Steady-State Approach. 9.3 Limitations of Network Modeling. 9.4 Example 1: Steady-State Model. 9.5 Example 2: Steady-State Model on Bacillus Data. 9.6 Example 3: Linear Time-Series Model. 9.7 Further Reading. 10. Molecular Classifiers. 10.1 Feature Selection. 10.2 Validation. 10.3.1 Nearest Neighbor. 10.3.2 Nearest Centroid. 10.3.3 Neural Networks. 10.3.4 Support Vector Machine. 10.4 Performance Evaluation. 10.5 Example I: Classification of Bladder Cancer Subtypes. 10.6 Example II: Classification of SRBCT Cancer Subtypes. 10.7 Summary. 10.8 Further Reading. 11. The Design of Probes for Arrays. 11.1 Selection of Genes for an Array. 11.2 Gene Finding. 11.3 Selection of Regions Within Genes. 11.4 Selection of Primers for PCR. 11.4.1 Example: Finding PCR Primers for Gene AF105374. 11.5 Selection of Unique Oligomer Probes. 11.6 Remapping of Probes. 11.7 Further Reading. 12. Genotyping and Resequencing Chips. 12.1 Example: Neural Networks for GeneChip Prediction. 12.2 Further Reading. 13. Experiment Design and Interpretation of Results. 13.1 Factorial Designs. 13.2 Designs for Two-Channel Arrays. 13.3 Hypothesis Driven Experiments. 13.4 Independent Verification. 13.5 Interpretation of Results. 13.6 Limitations of Expression Analysis. 13.6.1 Relative Versus Absolute RNA Quantification. 13.7 Further Reading. 14. Software Issues and Data Formats. 14.1 Standardization Efforts. 14.2 Databases. 14.3 Standard File Format. 14.4 Software for Clustering. 14.4.1 Example: Clustering with ClustArray. 14.5 Software for Statistical Analysis. 14.5.1 Example: Statistical Analysis with R. 14.5.2 The Affy Package of Bioconductor. 14.5.3 Commercial Statistics Packages. 14.6 Summary. 14.7 Further Reading. Appendix A: Web Resources: Commercial Software Packages. References. Index.
£73.76
John Wiley & Sons Inc DrugDNA Interactions
Book SynopsisLearn vital information about drug-DNA interactions from Drug-DNA Interactions: Structures and Spectra, the only comprehensive book written about this topic. Understand the types of structural and bonding information that can be obtained using specific physico-chemical methods and discover how to design new drugs that are more effective than current treatments and have fewer side effects. Find detailed information about X-ray crystallography, NMR spectroscopy, molecular modeling, and optical spectroscopy such as UV-Visible absorption, fluorescence, circular dichroism (CD), flow linear dichroism (FLD), infrared (IR) and Raman spectroscopy.Table of ContentsPreface. Introduction. 1. DNA Structures and Spectra. 1.1. DNA Structures. 1.2. Electronic Spectra. 1.3. Vibrational Spectra. 1.4. NMR Spectra. 1.5. Electron Spin Resonance Spectra. 1.6. X-Ray Crystallography. 1.7. Molecular Modeling an molecular Mechanics. 2. Intercalating Drugs. 2.1. Acridine Dyes. 2.2. Ethidium Bromide. 2.3. Aclacinomycin. 2.4. Sequence Preference. 2.5. Bis- and Tris- Intercalators. 3. Groove- Binding Drugs. 3.1. Netropsin and Distamycin. 3.2. Derivatives of Netropsin and Distamycin. 3.3. Hoechst 33258, SN6999, and their Derivatives. 3.4. Chromomycin, Mithramycin, and Other GC Binders. 3.5. Groove Binding and Intercalation. 4. Covalent Bonding Drugs. 4.1. (+) CC1065 and Related Drugs. 4.2. Anthramycin and Tomaymycin. 4.3. Ecteinascidins. 4.4. Mitomycins. 4.5. Intercalating Alkylators. 5. Strand-Breaking Drugs. 5.1. Bleomycins. 5.2. Enediyne Antibiotics. 6. Metal-Containing Drugs. 6.1. Cisplatin. 6.2. Cisplatin Derivatives. 6.3. Transplatin and Derivatives. 6.4. Monofunctional Platinum Complexes. 6.5. Polynuclear and High-valent Platinum Complexes. 6.6. Complexes Containing Other Metals. Appendixes. Index.
£143.40
The University of Michigan Press The DNA Mystique
Book SynopsisTrade ReviewThe DNA Mystique is a wake-up call to all who would dismiss America's love affair with 'the gene' as a merely eccentric obsession." —In These Times"Nelkin and Lindee are to be warmly congratulated for opening up this intriguing field [of genetics in popular culture] to further study." —Nature
£22.75
University of California Press dna
Book SynopsisThe genetic revolution has provided incredibly valuable information about our DNA, information that can be used to benefit and inform - but also to judge, discriminate, and abuse. This book gives the background information critical to understanding how genetics is affecting our everyday lives.Trade Review"Goes a long way toward exploring these issues in a painstaking yet readable scholarly treatise... Throughout, they make a convincing case that we are not our genome alone." New England Journal Of Medicine "The book is anything but dry reporting... An enjoyable and stimulating read for specialists in the field and the curious public alike." Science (AAAS) "Readers will come away with a realistic and encouraging perspective on medical genetics, providing that neither fantastic optimism nor abject fear is necessary to make the true story of DNA exciting." Qtly Review Of Biology "Readers will come away with a realistic and encouraging perspective on medical genetics, proving that neither fantastic optimism nor abject fear is necessary to make the true story of DNA exciting." Qtly Review Of BiologyTable of ContentsForeword by Victor A. McKusick Acknowledgments 1. DNA Sequence Does Not Equal Destiny 2. What Is Genomics? 3. Genetic Determinism 4. The Evolution and Deconstruction of Human-Centered Biology 5. Race and Ethnicity: Your History Is Written in Your Genes 6. Gender as a Spectrum, Not a Dichotomy 7. Genome-Based Forensics 8. When Genes Belong to Groups and Not Individuals 9. Genes as Commodities: Ownership of Genes by Business Interests 10. Protection against Genetic Discrimination: The New Civil Right 11. Reproductive Technologies: On the Road to Designer Babies? 12. Reproductive Cloning: From Farm Animals to Pets to Humans? 13. Therapeutic Cloning and Regenerative Medicine 14. Gene Therapy: Can the Promise Be Fulfilled? 15. Large Population Assessments: The Foundation for Genomic Medicine 16. Hidden Destiny: Unbounded by Your DNA Bibliography Illustration Credits Index
£21.25
Cambridge University Press Evolution of PlantPollinator Relationships 81 Systematics Association Special Volume Series Series Number 81
Book SynopsisWhat are the evolutionary mechanisms and ecological implications behind a pollinator choosing its favourite flower? Sixty-five million years of evolution has created the complex and integrated system which we see today and understanding the interactions involved is key to environmental sustainability. Examining pollination relationships from an evolutionary perspective, this book covers both botanical and zoological aspects. It addresses the puzzling question of co-speciation and co-evolution and the complexity of the relationships between plant and pollinator, the development of which is examined through the fossil record. Additional chapters are dedicated to the evolution of floral displays and signalling, as well as their role in pollination syndromes and the building of pollination networks. Wide-ranging in its coverage, it outlines current knowledge and complex emerging topics, demonstrating how advances in research methods are applied to pollination biology.Table of ContentsPreface; 1. Macroevolution for plant reproductive biologists Paul Wilson; 2. Pollination crisis, plant sex systems and predicting evolutionary trends in attractiveness Tom J. de Jong; 3. Evolution and ecological implications of 'specialized' pollinator rewards W. Scott Armbruster; 4. Fig-fig wasp mutualism, the fall of the strict co-speciation paradigm? Astrid Cruaud, James Cook, Yang Da-Rong, Gwenaëlle Genson, Roula Jabbour-Zahab, Finn Kjellberg, Rodrigo Augusto Santinelo Pereira, Nina Rønsted, Otilene Santos-Mattos, Vincent Savolainen, Rosichon Ubaidillah, Simon van Noort, Peng Yan-Qiong and Jean-Yves Rasplus; 5. Fossil bees and their plant associates Denis Michez, Maryse Vanderplanck and Michael S. Engel; 6. Pollen evidence for the pollination biology of early flowering plants Shusheng Hu, David L. Dilcher and David Winship Taylor; 7. Pollinator mediated floral divergence in the absence of pollinator shifts Allan G. Ellis and Bruce Anderson; 8. Animal pollination and speciation in plants: general mechanisms and examples from the orchids Florian P. Schiestl; 9. Why are floral signals complex? An outline of functional hypotheses Anne S. Leonard, Anna Dornhaus and Daniel R. Papaj; 10. A survey on pollination modes in cacti and a potential key innovation Boris O. Schlumpberger; 11. Zygomorphy, area and the latitudinal biodiversity gradient in angiosperms Jana C. Vamosi and Steven M. Vamosi; 12. Ambophily and 'super generalism' in Ceratonia siliqua (Fabaceae) pollination Amots Dafni, Talya Marom-Levy, Andreas Jürgens, Stefan Dötterl, Yuval Shimrat, Achik Dorchin, H. Elizabeth Kirkpatrick and Taina Witt; 13. Structure and dynamics of pollination networks: the past, the present and the future Jens M. Olesen, Yoko L. Dupont, Melanie Hagen, Claus Rasmussen and Kristian Trøjelsgaard; 14. Pollinators as drivers of plant distribution and assemblage into communities Loïc Pellissier, Nadir Alvarez and Antoine Guisan; 15. Effects of alien species on plant-pollinator interactions: how can native plants adapt to changing pollination regimes? Gideon Pisanty and Yael Mandelik; 16. Pollen resources of non-Apis bees in southern Africa Michael Kuhlmann and Connal D. Eardley; 17. Advances in the study of the evolution of plant-pollinator relationships Sébastien Patiny; Index.
£98.80
Cambridge University Press Biological Sequence Analysis Probabilistic Models of Proteins and Nucleic Acids
Book SynopsisProbabilistic models are becoming increasingly important in analysing the huge amount of data being produced by large-scale DNA-sequencing efforts such as the Human Genome Project. For example, hidden Markov models are used for analysing biological sequences, linguistic-grammar-based probabilistic models for identifying RNA secondary structure, and probabilistic evolutionary models for inferring phylogenies of sequences from different organisms. This book gives a unified, up-to-date and self-contained account, with a Bayesian slant, of such methods, and more generally to probabilistic methods of sequence analysis. Written by an interdisciplinary team of authors, it aims to be accessible to molecular biologists, computer scientists, and mathematicians with no formal knowledge of the other fields, and at the same time present the state-of-the-art in this new and highly important field.Trade Review'This book fills an important gap in the bioinformatics literature and should be required reading for anyone who is interested in doing serious work in biological sequence analysis. For biologists who have little formal training in statistics or probability, it is a long-awaited contribution that, short of consulting a professional statistician who is well versed in molecular biology, is the best source of statistical information that is relevant to sequence-alignment problems. This book seems destined to become a classic. I highly recommend it.' Andrew F. Neuwald, Trends in Biochemical Sciences'This book is a nice tutorial and introduction to the field and can certainly be recommended to all who wish to analyse biological sequences with computer methods. It can also serve as a basis for a university course for undergraduates.' Trends in Cell Biology' … an enjoyable opportunity to see a blend of modeling and data analysis at work on an important class of problems in the rapidly growing field of computational biology.' D. Siegmund, Short Book ReviewsTable of Contents1. Introduction; 2. Pairwise sequence alignment; 3. Multiple alignments; 4. Hidden Markov models; 5. Hidden Markov models applied to biological sequences; 6. The Chomsky hierarchy of formal grammars; 7. RNA and stochastic context-free grammars; 8. Phylogenetic trees; 9. Phylogeny and alignment; Index.
£55.99
Pearson Education Introduction to Quantitative Genetics
Book SynopsisThis classic text continues to provide the basis for understanding genetic principles behind quantitative differences, and extends these concepts to the segregation of genes that cause genetic variation in quantitative traits.Table of Contents Genetics Constitution of a Population Changes of Gene Frequency Small Populations: I Changes of Gene Frequency Under Simplified Conditions Small Populations: II Less Simplified Conditions Small Populations: III Pedigreed Populations and Close Inbreeding Continuous Variation Values and Means Variance Resemblance Between Relatives Heritability Selection: I The Results of Experiments Selection: III Information from Relatives Inbreeding and Crossbreeding: I Changes of Mean Value Inbreeding and Crossbreeding: II Changes of Variance Inbreeding and Crossbreeding: III Applications Scale Threshold Characters Correlated Characters Metric Characters under Natural Selection Quantitative Trait Loci
£60.99
Harvard University Press Life from an RNA World
Book SynopsisA majority of evolutionary biologists believe that we now can envision our biological predecessors - not the first, but nearly the first, living beings on Earth. This title is about these vanished forebears, sketching them in the distant past just as their workings first began to resemble our own.Trade ReviewLife from an RNA World is an unconventional book about RNA. Rather than opening with the central dogma and attendant teachings on molecular biology, Yarus uses evolution as a gateway. He then takes us on a journey through evolutionary time, concentrating on the roles of the various forms of RNA… [He] is a proficient guide. -- Tim Harris * Nature *Although precise historical details of the particular origin of life on Earth are probably unknowable, most scientists agree that a world existed in which RNA performed the duties of both genes and enzymes. This RNA world in turn evolved into the DNA–RNA–protein world of today. Michael Yarus’s Life from an RNA World offers an engaging introduction to the subject… Recent discoveries make Yarus’s book particularly timely, especially as a light-hearted introduction for scientifically minded readers outside the field. His chatty prose conveys the voice of a tour guide on a journey through the RNA world, introducing essential evolutionary and molecular biology and pointing out must-not-miss attractions. Even members of the origins-of-life community may appreciate his whimsical explanations of familiar phenomena. -- Irene A. Chen * Science *Michael Yarus’ book is a very enjoyable read, be the reader a well informed molecular biologist, or a lay person… Surely this book will highlight and increase the interest in the RNA world; raising the awareness that we are all, after all, the children of RNA. -- Michael Ladomery * Chemistry World *Yarus captivates with skilled character development—but here, the ‘characters’ are the prebiotic molecules that gave rise to everything that has ever lived or is alive today on our planet. -- Thomas Cech, Distinguished Professor, University of Colorado–Boulder, and 1989 Nobel Laureate in ChemistryTable of Contents* Introduction to Your Ancestor * Before We Begin: A Voluntary Chapter * Framing the Problem: The Buffalo and the Bacterium * The Big Tree: No Jackalopes Please * A Dance of Atoms * Allegro Agitato: The Origin of Life * The Winds That Blow through the Starry Ways * Tornados in a Junkyard * Between Genomes and Creatures * A Thumbnail Molecular Biology * RNA Structure: A Tape with a Shape * Intimations of an RNA World * The Experimentally Impaired Sciences * Test Tube RNA Evolution: First Light * Selection Amplification: Interrogating RNA's Possibilities * RNA Duplication: Replicase Activity in Real RNAs * RNA Capabilities and the Origins of Translation * The Quest for the Peptidyl Transferase * A Language Much Older Than Hieroglyphics: The Genetic Code * Assume a Spherical Cow: The Ribocyte * The Future of the RNA World * Lexicon * Index
£18.86
Prentice Hall (a Pearson Education company) The Double Helix A Personal Account of the
Book SynopsisThe classic personal account of Watson and Crick’s groundbreaking discovery of the structure of DNA, now with an introduction by Sylvia Nasar, author of A Beautiful Mind.By identifying the structure of DNA, the molecule of life, Francis Crick and James Watson revolutionized biochemistry and won themselves a Nobel Prize. At the time, Watson was only twenty-four, a young scientist hungry to make his mark. His uncompromisingly honest account of the heady days of their thrilling sprint against other world-class researchers to solve one of science’s greatest mysteries gives a dazzlingly clear picture of a world of brilliant scientists with great gifts, very human ambitions, and bitter rivalries. With humility unspoiled by false modesty, Watson relates his and Crick’s desperate efforts to beat Linus Pauling to the Holy Grail of life sciences, the identification of the basic building block of life. Never has a scientist been so truthful in cap
£22.10
Hill & Wang Inc.,U.S. The Stuff of Life A Graphic Guide to Genetics and DNA
Book SynopsisLet''s face it: From adenines to zygotes, from cytokinesis to parthenogenesis, even the basics of genetics can sound utterly alien. So who better than an alien to explain it all? Enter Bloort 183, a scientist from an asexual alien race threatened by disease, who''s been charged with researching the fundamentals of human DNA and evolution and laying it all out in clear, simple language so that even his slow-to-grasp-the-point leader can get it. In the hands of the award-winning writer Mark Schultz, Bloort''s predicament becomes the means of giving even the most science-phobic reader a complete introduction to the history and science of genetics that''s as easy to understand as it is entertaining to read.
£14.25
John Wiley and Sons Ltd Equine Genomics
Book SynopsisThe complete mapping of the horse genome sequence makes a significant contribution to understanding equine biology. This book provides a timely comprehensive overview of equine genomic research.Trade Review“Equine Genomicsis an excellent text that compiles historical accomplishments in equine genetics and molecular biology, describes state-of-theart approaches to understanding the equine genome, and provides glimpses of where the field may go in the future . . . It is our responsibility to try to keep up, and I believe this book will help us do that.” (Journal of the American Veterinary Medical Association, 15 June 2014)Table of ContentsContributors ix Preface xi Chapter 1 Defining the equine genome: The nuclear genome and the mitochondrial genome 1Bhanu P. Chowdhary Chapter 2 Genetic linkage maps 11June Swinburne and Gabriella Lindgren Chapter 3 Physical and comparative maps 49Terje Raudsepp and Bhanu P. Chowdhary Chapter 4 The Y-chromosome 73Terje Raudsepp, Nandina Paria, and Bhanu P. Chowdhary Chapter 5 Unexpected structural features of the equine major histocompatibility complex 93Loren C. Skow and Candice L. Brinkmeyer-Langford Chapter 6 Assembly and analysis of the equine genome sequence 103Claire M. Wade Chapter 7 Genomic tools and resources: Development and applications of an equine SNP genotyping array 113Molly McCue and Jim Mickelson Chapter 8 Functional genomics 125Stephen J. Coleman, Michael J. Mienaltowski, and James N. MacLeod Chapter 9 Coat color genomics 143Samantha A. Brooks and Rebecca R. Bellone Chapter 10 Genomics of skin disorders 155Amy E. Young, Stephen D. White, and Danika L. Bannasvch Chapter 11 Genomics of muscle disorders 171James R. Mickelson, Stephanie J. Valberg, Carrie J. Finno, and Molly E. McCue Chapter 12 Genomics of skeletal disorders 187Ottmar Distl Chapter 13 Genomics of reproduction and fertility 199Terje Raudsepp, Pranab J. Das and Bhanu P. Chowdhary Chapter 14 Genetics of equine neurologic disease 217Carrie J. Finno and Monica Aleman Chapter 15 Molecular genetic testing and karyotyping in the horse 241M. C. T. Penedo and Terje Raudsepp Chapter 16 Genomics of laminitis 255Jim K. Belknap Chapter 17 Genomics of performance 265Emmeline W. Hill, Lisa M. Katz, and David E. MacHugh Chapter 18 Genomics of the circadian clock 285Barbara A. Murphy Chapter 19 Mitochondrial genome: Clues about the evolution of extant equids and genomic diversity of horse breeds 311Cynthia C. Steiner, Kateryna D. Makova, and Oliver A. Ryder Index 323
£137.66
Taylor & Francis Inc In Situ Hybridization in Electron Microscopy
Book SynopsisIn situ hybridization is a technique that allows for the visualization of specific DNA and RNA sequences in individual cells, and is an especially important method for studying nucleic acids in heterogeneous cell populations. in situ Hybridization in Electron Microscopy reviews the three main methods developed for the ultrastructural visualization of genes: hybridization on ultrathin sections of tissue embedded in hydrophilic resin (post-embedding method) hybridization prior to embedding (pre-embedding) hybridization on ultrathin sections of frozen tissue (frozen tissue method). For each technique, the different stages are described in detail: the preparation of tissue, pretreatment, hybridization, and visualization of the hybridization products. The book combines theory and practice, starting with the basic principles, then breaking down the experimental process into successive steps illustrated by numerous diagrams, detailed protocols, and tables. This is aTable of ContentsGeneral Introduction. Abbreviations. Probes. Principles of Methodology. Sample Preparation. Post-Embedding Technique. Pre-Embedding Technique. Frozen Tissue Technique. Semithin Sections. Controls and Problems. Examples of Results. Appendices. Glossary. Index.
£204.25
Taylor & Francis Inc DNA Methylation
Book SynopsisDNA Methylation: Approaches, Methods and Applications describes the relation DNA methylation has to gene silencing in disease, and explores its promising role in treating cancer. Written by leaders in the field, this exceptional compilation of articles outlines the best techniques to use when addressing questions concerning the cytosine methylation status of genomic DNA. It includes concepts, experimental models, and clinical uses of demethylating agents. The book provides a balance between articles clarifying methodological details and more general review chapters that offer broad biological perspectives on DNA methylation. This is an invaluable handbook for researchers and clinicians interested in genetics and molecular biology, particularly epigenetic therapies and gene silencing.Trade Review"… written by leaders in the field. … interesting for both researchers and clinicians. It is an excellent summary of the subject for scientists starting in the field of epigenetics and it is also a reference book for professionals already familiar with the subject." – Assam El-Osta, Baker Heart Research Institute, Australia in CHEMMEDCHEM, 3, 2008Table of ContentsDescribing the relation DNA methylation has to gene silencing in disease, this book explores its promising role in treating cancer. Written by leaders in the field, it outlines the best techniques to use when addressing questions concerning the cytosine methylation status of genomic DNA. Including concepts, experimental models, and clinical uses of demethylating agents, the book provides articles clarifying methodological details and more general review chapters that offer broad biological perspectives on DNA methylation. This is an invaluable handbook for researchers and clinicians interested in genetics and molecular biology, particularly epigenetic therapies and gene silencing.
£209.00
Taylor & Francis Inc Comparative Genomics
Book Synopsis When genomic research first came on the scene, much of the biomedical research community viewed it as a limited venture with limited potential. We now know that such an assessment was both highly premature and wonderfully inaccurate. In the last ten years, we've witnessed such remarkable acceleration in the merger of basic and applied genomic research that, among other things, genomic research is now thought of as being intrinsic to current drug research. Through rigorous comparative analysis, the genomes of cold-blooded vertebrate, avian, and other mammalian species are providing a deeper understanding of the human genome. Moreover, genomic sequences, which are becoming available for several species have proven to be highly relevant to drug research with regard to a number of otherwise intractable conditions. Rather than offering a comprehensive volume covering every aspect of comparative genomics, Comparative Genomics: Basic and Applied Research embodies the diverse Table of ContentsIntroduction. Basic Research. Applied Research
£190.00
Cold Spring Harbor Laboratory Press,U.S. An A to Z of DNA Science
Book Synopsis
£12.24
Cold Spring Harbor Laboratory Press,U.S. Gene Machines
£8.79
Cold Spring Harbor Laboratory Press,U.S. DNA Replication and Human Disease
Book Synopsis
£82.65
Cold Spring Harbor Laboratory Press,U.S. Untangling the Double Helix
Book Synopsis
£48.45
Cold Spring Harbor Laboratory Press,U.S. Untangling the Double Helix
Book Synopsis
£27.55
Springer-Verlag New York Inc. Proteomics in Systems Biology
Book SynopsisThis detailed book highlights the diverse techniques and applications of proteomics in an accessible, informative, and concise manner.Table of Contents1. Review of the Real and Sometimes Hidden Costs in Proteomics Experimental Workflows Aicha Asma Houfani and Leonard James Foster 2. High-Throughput Mass Spectrometry-Based Proteomics with dia-PASEF Patricia Skowronek and Florian Meier 3. Isolation of Detergent Insoluble Proteins from Mouse Brain Tissue for Quantitative Analysis Using Data Independent Acquisition (DIA) Cristen Molzahn, Lorenz Nierves, Philipp F. Lange, and Thibault Mayor 4. Rodent Lung Tissue Sample Preparation and Processing for Shotgun Proteomics Hadeesha Piyadasa, Ying Lao, Oleg Krokhin, and Neeloffer Mookherjee 5. Protein Purification and Digestion Methods for Bacterial Proteomic Analyses Nicole Hansmeier, Samrachana Sharma, and Tzu-Chiao Chao 6. Mapping Cell Surface Proteolysis with Plasma Membrane-Targeted Subtiligase Aspasia A. Amiridis and Amy M. Weeks 7. N-Terminomics/TAILS of Tissue and Liquid Biopsies Anthonia Anowai, Sameeksha Chopra, Barbara Mainoli, Daniel Young, and Antoine Dufour 8. HUNTER: Sensitive Automated Characterization of Proteolytic Systems by N Termini Enrichment from Microscale Specimen Anuli C. Uzozie, Janice Tsui, and Philipp F. Lange 9. Phosphoproteomics and Organelle Proteomics in Pancreatic Islets Özum Sehnaz Caliskan, Giorgia Massacci, Natalie Krahmer, and Francesca Sacco 10. Phosphoproteomic Sample Preparation for Global Phosphorylation Profiling of a Fungal Pathogen Brianna Ball, Jonathan Krieger, and Jennifer Geddes-McAlister 11. Glycopeptide-Centric Approaches for the Characterization of Microbial Glycoproteomes Nichollas E. Scott 12. Integrated Network Discovery Using Multi-Proteomic Data Rafe Helwer and Vincent C. Chen 13. Targeted Cross-Linking Mass Spectrometry on Single-Step Affinity Purified Molecular Complexes in the Yeast Saccharomyces cerevisiae Christian Trahan and Marlene Oeffinger 14. A Crosslinking – Mass Spectrometry Protocol for the Structural Analysis of Microtubule-Associated Proteins Atefeh Rafiei and David C. Schriemer 15. Comprehensive Interactome Mapping of Nuclear Receptors Using Proximity Biotinylation Lynda Agbo, Sophie Anne Blanchet, Pata-Eting Kougnassoukou Tchara, Amélie Fradet-Turcotte, and Jean-Philippe Lambert 16. Mining Proteomics Datasets to Uncover Functional Pseudogenes Anna Meller and François-Michel Boisvert 17. Proteomic Profiling of the Interplay between a Bacterial Pathogen and Host Uncovers Novel Anti-Virulence Strategies Arjun Sukumaran and Jennifer Geddes-McAlister 18. Affinity-Enrichment of Salmonella-Modified Membranes from Murine Macrophages for Proteomic Analyses Tzu-Chiao Chao, Samina Thapa, and Nicole Hansmeier 19. Proteomic Profiling of Interplay between Agrobacterium tumefaciens and Nicotiana benthamiana for Improved Molecular Pharming Outcomes Nicholas Prudhomme, Jonathan R. Krieger, Michael D. McLean, Doug Cossar, and Jennifer Geddes-McAlister 20. Label-Free Quantitative Proteomic Profiling of Fusarium Head Blight in Wheat Boyan Liu, Danisha Johal, Mitra Serajazari, and Jennifer Geddes-McAlister 21. DIA Proteomics and Machine Learning for the Fast Identification of Bacterial Species in Biological Samples Florence Roux-Dalvai, Mickaël Leclercq, Clarisse Gotti, and Arnaud Droit 22. Novel Bioinformatics Strategies Driving Dynamic Metaproteomic Studies Caitlin M.A. Simopoulos, Daniel Figeys, and Mathieu Lavallée-Adam 23. MaxQuant Module for the Identification of Genomic Variants Propagated into Peptides Pavel Sinitcyn, Maximilian Gerwien, and Jürgen Cox 24. Untargeted Metabolomic Profiling of Fungal Species Populations Thomas E. Witte and David P. Overy
£151.99
Springer-Verlag New York Inc. Systems Medicine
Book SynopsisThis volume explores the latest technological advances and covers all facets of systems medicine with respect to precision medicine. The chapters in this book are organized into four parts. Part One highlights the recent achievements in proteomics for biomarkers identification, integration of omics and phenotypic data for precision medicine, and medicine-guided treatment of drug-induced Stevens-Johnson syndrome. Part Two covers systems-based computational approaches for pharmaceutical research and drug development, the principle of optimizing systemic exposure of drugs, and Animal Rule for drug repurposing. Part Three looks at computational tools and methodologies of network biology, quantitative systems toxicology, and modeling and stimulating patient response variabilities. Part Four talks about how systems medicine can address unmet medical and health needs, and identify educational needs. Written in the highly successful Methods in Molecular Biology series format, chapters include Table of ContentsAcknowledgements…Preface…Table of Contents…Contributing Authors…Part I Scientific and Medical Advances1. Mass Spectrometry-Based Proteomics for Biomarker DiscoveryZhijun Cao and Li-Rong Yu2. Integration of Omics and Phenotypic Data for Precision MedicineJuan Zhao, QiPing Feng, and Wei-Qi Wei3. Stevens-Johnson Syndrome and Toxic Epidermal Necrolysis in the Era of Systems MedicineChun-Bing Chen, Chuang-Wei Wang, and Wen-Hung ChungPart II Acceleration of Pharmaceutical Research and Development4. Integration of Engineered Delivery with the Pharmacokinetics of Medical Candidates via Physiology-Based PharmacokineticsYuching Yang and Xinyuan Zhang5. Applications of Quantitative System Pharmacology Modeling to Model Informed Drug DevelopmentAndy Z.X. Zhu and Mark Rogge6. Combating Viral Diseases in the Era of Systems MedicineJane P.F. Bai and Ellen Y. Guo7. Toxicity Analysis of Pentachlorophenol Data with a Bioinformatics Tool SetNatalia Polouliakh, Takeshi Hase, Samik Ghosh, and Hiroaki KitanoPart III Tools and Methodologies8. Virtual Populations for Quantitative Systems Pharmacology ModelsYougan Cheng, Ronny Straube, Abed E. Alnaif, Lu Huang, Tarek A. Leil, and Brian J. Schmidt9. Quantitative Systems Toxicology and Drug Development: The DILIsym ExperiencePaul B. Watkins10. Introduction to Genomic Network Reconstruction for Cancer ResearchGuillermo de Anda Jáuregui, Hugo Tovar, Segio Alcalá-Corona, Enrique Hernández-Lemus11. Learning in Medicine: The Importance of Statistical ThinkingMassimiliano Russo and Bruno Scarpa12. Development and Applications of Interoperable Biomedical Ontologies for Integrative Data and Knowledge Representation and Multiscale Modeling in Systems MedicineYongqun HePart IV Systems Medicine to Address Unmet Medical Needs13. Systems Biology to Address Unmet Medical Needs in Neurological DisordersMasha G. Savelieff, Mohamed H. Noureldein, and Eva L. Feldman14. Informatics in Medical Product Regulation: The Right Drug at the Right Dose for the Right PatientEileen Navarro Almario, Anna Kettermann, and Vaishali Popat15. Personal Dense Dynamic Data Clouds Connect Systems Bio-Medicine to Scientific WellnessGilbert S. Omenn, Andrew T. Magis, Nathan D. Price, and Leroy Hood16. Educational Needs for Quantitative Systems Pharmacology ScientistsJames M. GalloSubject Index List…
£143.99
Springer-Verlag New York Inc. PhaseSeparated Biomolecular Condensates
Book SynopsisThis volume provides readers with a broad collection of theoretical, computational, and experimental methods to quantitatively study the properties of phase-separate biomolecular condensates in diverse systems. The chapters in this book cover topics such as theoretical and computational methods; methods for in vitro characterization of biomolecular condensates; and techniques that enable in-cell characterization of biomolecular condensates. Written in the highly successful Methods in Molecular Biology series format, chapters include introduction to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and expert tips on troubleshooting and avoiding known pitfalls.Comprehensive and thorough, Phase-Separated Biomolecular Condensates: Methods and Protocols is a valuable resource that helps researchers learn and use established methods to study both biophysical properties and biological funcTable of ContentsPreface…Table of Contents…Contributing Authors…1. Calculating Binodals and Interfacial Tension of Phase-Separated Condensates from Molecular Simulations, with Finite-Size CorrectionsKonstantinos Mazarakos, Sanbo Qin, and Huan-Xiang Zhou2. Field-Theoretic Simulation Method to Study the Liquid-Liquid Phase Separation of PolymersSaeed Najafi, James McCarty, Kris T. Delaney, Glenn H. Fredrickson, and Joan-Emma Shea3. Numerical Techniques for Applications of Analytical Theories to Sequence-Dependent Phase Separations of Intrinsically Disordered ProteinsYi-Hsuan Lin, Jonas Wessén, Tanmoy Pal, Suman Das, and Hue Sun Chan4. An Introduction to the Stickers-and-Spacers Framework as Applied to Biomolecular CondensatesGarrett M. Ginell and Alex S. Holehouse5. Multi-Scale Modeling of Protein-RNA Condensation In and Out of EquilibriumRabia Laghmach, Isha Malhotra, and Davit A. Potoyan6. Fluorescence Lifetime Imaging Microscopy of Biomolecular CondensatesMy Diem Quan. Shih-Chu Leff Liao, Josephine C. Ferreon, and Allan Chris M. Ferreon7. Single-Molecule Fluorescence Methods to Study Protein-RNA Interactions Underlying Biomolecular CondensatesLaura R. Ganser, Yingda Ge, and Sua Myong8. Fluorescence Correlation Spectroscopy and Phase SeparationJuan Jeremías Incicco, Debjit Roy, Melissa D. Stuchell-Brereton, and Andrea Soranno9. Measurement of Protein and Nucleic Acid Diffusion Coefficients within Biomolecular Condensates Using In-Droplet Fluorescence Correlation SpectroscopyIbraheem Alshareedah and Priya R. Banerjee10. Single-Molecule Imaging of the Phase Separation-Modulated DNA Compaction to Study Transcriptional RepressionLinyu Zuo, Luhua Lai, and Zhi Qi11. Phase Separation-Based Biochemical Assays for Biomolecular InteractionsGaofeng Pei, Min Zhou, Weifan Xu, Jing Wang, and Pilong Li12. Determining Thermodynamic and Material Properties of Biomolecular Condensates by Confocal Microscopy and Optical TweezersArchishman Ghosh, Divya Kota, and Huan-Xiang Zhou13. A High-Throughput Method to Profile Protein Liquid-Liquid Phase SeparationYichen Li, Jinge Gu, Cong Liu, and Dan Li14. Phase Separation of Rubisco by the Folded SSUL Domains of CcmM in Beta-Carboxysome BiogenesisHuping Wang and Manajit Hayer-Hartl15. Cryo-Electron Tomography of Reconstituted Biomolecular CondensateFergus Tollervey, Xiaojie Zhang, Mainak Bose, Jenny Sachweh, Jeffrey B. Woodruff, Titus M. Franzmann, and Julia Mahamid16. Sedimentation Assays to Assess the Impact of Post-Translational Modifications on Phase Separation of RNA-Binding Proteins In Vitro and In CellsLara A. Gruijs da Silva and Dorothee Dormann17. Synthetic Organelles for Multiple mRNA Selective Genetic Code Expansion in EukaryotesChristopher D. Reinkemeier and Edward A. Lemke18. Single Molecule Tracking of RNA Polymerase In and Out of Condensates in Live Bacterial Cells Baljyot Singh Parmar and Stephanie C. Weber19. An Optogenetic Toolkit for the Control of Phase Separation in Living CellsChaelim Kim and Yongdae Shin20. Assessing the Phase Separation Propensity of Proteins in Living Cells Through Optodroplet Formation Anne Rademacher, Fabian Erdel, Robin Weinmann, and Karsten Rippe21. Mass Balance Imaging: A Phase Portrait Analysis for Characterizing Growth Kinetics of Biomolecular Condensates Jan Giesler, Victoria Tianjing Yan, Stephan Grill, and Arjun Narayanan22. Characterizing Properties of Biomolecular Condensates Below the Diffraction Limit In VivoGanesh Pandey, Alisha Budhathoki, and Jan-Hendrik SpilleSubject Index List…
£116.99
Springer-Verlag New York Inc. Transposable Elements
Book SynopsisThe volume presents a small selection of state-of-the-art approaches for studying transposable elements(TE). Chapters guide readers through HTS-based approaches, bioinformatic tools, methods to studyTE protein complexes, and the functional impact on the host. Written in the successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible protocols, and notes on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Transposable Elements: Methods and Protocols aims to be a useful practical guide to researches to help further their study in this field. Table of Contents1. An overview of best practices for transposable element identification, classification and annotation in eukaryotic genomes Fernando Rodriguez and Irina R. Arkhipova 2. Assembly-free annotation and quantification of transposable elements with dnaPipeTE Clément Goubert 3. Best practice for the identification of horizontally transferred transposons James D Galbraith, Zhipeng Qu, Atma M Ivancevic, David L Adelson 4. Genotyping of transposable elements insertions segregating in the human populations using short-read re-alignments Xun Chen, Guillaume Bourque, and Clément Goubert 5. A Pangenome approach to detect and genotype TE insertion polymorphisms Cristian Groza, Guillaume Bourque, and Clément Goubert 6. Experimental validation of transposable element insertions using the Polymerase Chain Reaction (PCR) Miriam Merenciano, Marta Coronado-Zamora, and Josefa González 7. Quantification of LINE-1 RNA expression from bulk RNA-seq using L1EM Wilson McKerrow 8. Genome-wide profiling of L1 DNA methylation by bs-ATLAS-seq Claude Philippe and Gael Cristofari 9. Nanopore epigenomic analysis of transposable element DNA modifications Nathan Smits and Geoffrey Faulkner 10. Targeted resequencing and methylation analysis of L1 elements by nanopore sequencing Arpita Sarkar, Sophie Lanciano, and Gael Cristofari 11. Inferring protein-DNA binding profiles at interspersed repeats using HiChIP and PatChER Darren Taylor and Miguel R Branco 12. Affinity-based Interactome Analysis of Endogenous LINE-1 Macromolecules Luciano H. Di Stefano, Leila Saba, Mehrnoosh Oghbaie, Hua Jiang, Wilson McKerrow, Maria Benitez-Guijarro, Martin S. Taylor, and John LaCava 13. LINE-1 retrotransposition assays in embryonic stem cells Marta Garcia-Canadas, Francisco Sanchez-Luque, Laura Sanchez, Johana Rojas, and Jose Garcia Perez 14. Detecting somatic transposable element insertions in Drosophila tissues Katarzyna Siudeja 15. Precise and scarless insertion of transposable elements by Cas9-mediated genome engineering” Vivien M Weber, Aurelien J Doucet, and Gael Cristofari 16. Epigenetic editing of transposable and repetitive elements Joanna M Jachowicz 17. Using CRISPR to investigate the regulatory activity of transposable elements David M Simpson, Conor R Kelly, and Edward B Chuong
£179.99
O'Reilly Media Consul Up and Running
Book SynopsisThis definitive guide shows you how to automate networking for simple and secure application delivery with Consul. Author Luke Kysow demonstrates how this service mesh solution provides a software-driven approach to security, observability, and traffic management.
£39.74
O'Reilly Media Genomics in the Azure Cloud
Book SynopsisThis practical guide bridges the gap between general cloud computing architecture in Microsoft Azure and scientific computing for bioinformatics and genomics.
£47.99
Cambridge University Press Bayesian Evolutionary Analysis with BEAST
Book SynopsisA comprehensive overview of Bayesian approaches to phylogenetics using Markov chain Monte Carlo (MCMC) methods, offering theoretical insight, pragmatic advice and tools to develop further models. This title is a one-stop reference to applying the latest phylogenetic models in BEAST 2, interpreting the analyses and extending these models further.Trade Review'Want to construct a phylogeny, add in calibrated time points or work out the past history of an epidemic? The open source package BEAST has established itself as the industry standard for all this and more. This definitive book, explaining what is under the hood, how the user can customize extensions and, most critically, a simple 'how to' users guide, is necessary reading for beginners and specialists alike.' Laurence D. Hurst, University of Bath'In concert with the dramatic improvements to DNA sequencing technology, Bayesian inference has revolutionized population genetics, phylogenetics, and divergence time estimation. A similar impact on epidemiology appears imminent via a suite of new Bayesian methods that incorporate host and pathogen DNA sequence data into established mathematical frameworks. This book is an accessible and thorough introduction to these Bayesian procedures. However, the book does far more than explain the theory. It also includes clear guides on how to use the BEAST 2 software for performing Bayesian analyses, and how to visualize the results. Because the software is designed to be extensible, the book instructs users to write their own code to supplement the diverse methods that are already implemented in BEAST 2. This book is timely and is written by two of the leaders of the field. I highly recommend it.' Jeff Thorne, North Carolina State UniversityTable of ContentsPreface; Acknowledgements; Part I. Theory: 1. Introduction; 2. Evolutionary trees; 3. Substitution and site models; 4. The molecular clock; 5. Structured trees and phylogeography; Part II. Practice: 6. Bayesian evolutionary analysis by sampling trees; 7. Setting up and running a phylogenetic analysis; 8. Estimating species trees from multilocus data; 9. Advanced analysis; 10. Posterior analysis and post-processing; 11. Exploring phylogenetic tree space; Part III. Programming: 12. Getting started with BEAST; 13. BEAST XML; 14. Coding and design patterns; 15. Putting it all together; Bibliography; List of authors; List of subjects.
£48.44
Cambridge University Press Computational Thinking for Life Scientists
Book SynopsisComputational thinking is increasingly gaining importance in modern biology, due to the unprecedented scale at which data is nowadays produced. Bridging the cultural gap between the biological and computational sciences, this book serves as an accessible introduction to computational concepts for students in the life sciences. It focuses on teaching algorithmic and logical thinking, rather than just the use of existing bioinformatics tools or programming. Topics are presented from a biological point of view, to demonstrate how computational approaches can be used to solve problems in biology such as biological image processing, regulatory networks, and sequence analysis. The book contains a range of pedagogical features to aid understanding, including real-world examples, in-text exercises, end-of-chapter problems, colour-coded Python code, and ''code explained'' boxes. User-friendly throughout, Computational Thinking for Life Scientists promotes the thinking skills and self-efficacy rTrade Review'An excellent and very gentle introduction to bioinformatics for biologists. In contrast to books that focus on algorithms and ignore programming or focus on programming without explaining algorithms, this book is a perfect blend of both algorithms and programming!' Pavel Pevzner, Ronald R. Taylor Chair and Distinguished Professor of Computer Science, University of California at San Diego'The ability to extract quantitative information from data is an essential skill for the modern biologist. In order to maximize the benefit of programming, use of existing computational tools and effective collaboration with computational scientists, biologists must be able to 'think computationally' by gaining a more algorithmic and logical thinking. In their book, Benny Chor and Amir Rubinstein introduce fundamental computational concepts to life sciences students. Each chapter covers a distinct computational idea motivated by a concrete biological challenge. Questions embedded throughout each chapter and code examples provide hands-on practice. Similarly to the way in which chemistry is perceived as being essential to the biology curriculum, computational thinking should also be considered a part of the modern biologist's basic training. This excellent book is essential reading for undergraduate life sciences students.' Assaf Zaritsky, Ben-Gurion University of the Negev, IsraelTable of ContentsIntroduction; Part I. Programming in Python: 1. Crash introduction to python; 2. Efficiency matters – gentle intro to complexity; Part II. Sequences: 3. Sets dictionaries and hashing; 4. Regular expressions and biological patterns; Part III. Networks: 5. Basic notions in graph theory; 6. Shortest paths and breadth first search; 7. Simulation of regulatory networks; Part IV. Images: 8. Digital images representation; 9. Image processing; Part V. Limitations of Computing: 10. Mission impossible; 11. Mission infeasible; Index.
£71.24
Cambridge University Press Why DNA
Book SynopsisInformation is central to the evolution of biological complexity, a physical system relying on a continuous supply of energy. Biology provides superb examples of the consequent Darwinian selection of mechanisms for efficient energy utilisation. Genetic information, underpinned by the Watson-Crick base-pairing rules is largely encoded by DNA, a molecule uniquely adapted to its roles in information storage and utilisation.This volume addresses two fundamental questions. Firstly, what properties of the molecule have enabled it to become the predominant genetic material in the biological world today and secondly, to what extent have the informational properties of the molecule contributed to the expansion of biological diversity and the stability of ecosystems. The author argues that bringing these two seemingly unrelated topics together enables Schrödinger''s What is Life?, published before the structure of DNA was known, to be revisited and his ideas examined in the context of our currenTrade Review'The essence of the book is in its title. The DNA structures and topology are described so clearly that the reader perceives these intricacies as pure evolutionary elegance, and understands WHY it is only in its balance of stability and agility that life could have started its journey. This book explains how DNA has become the fascinating prism, made of a fabric of complexity and information, into which the living reflects itself. My opinion is passionate because I have been thinking about the same problems for decades, and here I find many of the answers. Especially: what makes DNA so unique? It is a text that I keep reading over again.' Ernesto Di Mauro, IBPM, National Research Council, Rome'In What Is Life? Schrödinger conjectured that, in animate matter, order is derived from order, foreshadowing the discovery of DNA structure. Why DNA? is about this molecule and its dual information content - in linear genetic code and in thermodynamics of three-dimensional DNA structures. It addresses how DNA's intrinsic order led to complex, highly ordered living organisms, in a world that strives towards disorder. Why would DNA supplant RNA in carrying hereditary information during biological evolution? Why did multicellular organisms emerge, since natural selection favours the fittest, such as simple bacteria? What is complexity, and what has it to do with Bayesian logic? How do complexity, information and energy interrelate? This is a succinct discourse on Schrödinger's question, expanding from molecular interactions and genome cooperation to ecological systems and societal evolution. A must-read for biology scholars, and anyone interested in life's origins, biological evolution and the interface of biology and physics.' Georgi Muskhelishvili, Agricultural University of Georgia, TbilisiTable of ContentsAcknowledgements; Preface; 1. The perennial question; 2. The nature of information – information, complexity and entropy; 3. DNA – the molecule; 4. The evolution of biological complexity; 5. Cooperating genomes; 6. DNA, information and complexity; 7. Origins; 8. The complexity of societies; 9. Why DNA – and not RNA?; General reading and bibliography.
£26.25
Cambridge University Press Algorithmic Information Dynamics
Book SynopsisAimed at graduate students and researchers, this book offers a model-driven approach to the study and manipulation of dynamical systems. Based on an online course hosted by the Complexity Explorer, it uses analytical tools from information theory and complexity science to tackle key challenges in network and systems biology.Table of ContentsIntroduction; Part I. Preliminaries: 1. A computational approach to causality; 2. Networks: from structure to dynamics; 3. Information and computability theories; Part II. Theory and Methods: 4. Algorithmic information theory; 5. The coding theorem method (CTM); 6. The block decomposition method (BDM); 7. Graph and tensor complexity; 8. Algorithmic information dynamics (AID); Part III. Applications: 9. From theory to practice; 10. Algorithmic dynamics in artificial environments; 11. Applications to integer and behavioural sequences; 12. Applications to evolutionary biology; Postface; Appendix: Mutual and conditional BDM; Glossary.
£56.99
John Wiley & Sons Inc Exploration and Analysis of DNA Microarray and
Book SynopsisPraise for the First Edition extremely well writtena comprehensive and up-to-date overview of this important field. Journal of Environmental Quality Exploration and Analysis of DNA Microarray and Other High-Dimensional Data, Second Edition provides comprehensive coverage of recent advancements in microarray data analysis. A cutting-edge guide, the Second Edition demonstrates various methodologies for analyzing data in biomedical research and offers an overview of the modern techniques used in microarray technology to study patterns of gene activity. The new edition answers the need for an efficient outline of all phases of this revolutionary analytical technique, from preprocessing to the analysis stage. Utilizing research and experience from highly-qualified authors in fields of data analysis, Exploration and Analysis of DNA Microarray and Other High-Dimensional Data, Second Edition featurTrade Review“Featuring new information on interpretation of findings, class prediction, ABC clustering, limma for mixed models, biclustering, mass spectrometry, tracking Spearman correlations, and more, this \extremely well written" (Journal of Environmental Quality) book is a choice reference for scientists, teachers, and students interested in DNA data analysis.” (Zentralblatt MATH, 1 October 2014) “In summary this is an excellent text for both life scientist and computer/mathematicians. Highly recommended.” (Scientific Computing, 1 August 2014) Table of ContentsPreface xv Acknowledgments xvii 1 A brief introduction 1 1.1 A note on exploratory data analysis 3 1.2 Computing considerations and software 4 1.3 A brief outline of the book 5 1.4 Datasets and case studies 7 2 Genomics basics 11 2.1 Genes 11 2.2 DNA 12 2.3 Gene expression 13 2.4 Hybridization assays and other laboratory techniques 15 2.5 The human genome 16 2.6 Genome variations and their consequences 18 2.7 Genomics 19 2.8 The role of genomics in pharmaceutical and research and clinical practice 20 2.9 Proteins 23 2.10 Bioinformatics 23 3 Microarrays 27 3.1 Types of microarray experiments 28 3.2 A very simple hypothetical microarray experiment 32 3.3 A typical microarray experiment 34 3.4 Multichannel cDNA microarrays 38 3.5 Oligonucleotide microarrays 38 3.6 Bead based arrays 40 3.7 Confirmation of microarray results 40 4 Processing the scanned image 43 4.1 Converting the scanned image to the spotted image 44 4.2 Quality assessment 47 4.3 Adjusting for background 53 4.4 Expression level calculation for twochannel cDNA microarrays 56 4.5 Expression level calculation for oligonucleotide microarrays 58 5 Preprocessing microarray data 65 5.1 Logarithmic transformation 66 5.2 Variance stabilizing transformations 66 5.3 Sources of bias 68 5.4 Normalization 69 5.5 Intensity dependent normalization 70 5.6 Judging the success of a normalization 81 5.7 Outlier identification 83 5.8 Nonresistant rules for outlier identification 83 5.9 Resistant rules for outlier identification 83 5.10 Assessing replicate array quality 84 6 Summarization 95 6.1 Replication 95 6.2 Technical replicates 96 6.3 Biological replicates 100 6.4 Biological replicates 100 6.5 Multiple oligonucleotide arrays 102 6.6 Estimating fold change in twochannel experiments 104 6.7 Bayes estimation of fold change 105 6.8 Estimating fold change Affymetrix data 106 6.9 RMA Summarization of multiple oligonucleotide arrays revisited 107 6.10 FARMS summarization. 108 7 Two group comparative experiments 119 7.1 Basics of statistical hypothesis testing 120 7.2 Fold changes 123 7.3 The two sample t test 123 7.4 Diagnostic checks 127 7.5 Robust t tests 129 7.6 The Mann Whitney Wilcox on rank sum test 130 7.7 Multiplicity 132 7.8 The false discovery rate 135 7.9 Resampling based Multiple Testing Procedures 138 7.10 Small variance adjusted t tests and SAM 140 7.11 Conditional t 146 7.12 Borrowing strength across genes 149 7.13 Twochannel experiments 151 7.14 Filtering 153 8 Model based inference and experimental design considerations 177 8.1 The F test 178 8.2 The basic linear model 179 8.3 Fitting the model in two stages 181 8.4 Multichannel experiments 182 8.5 Experimental design considerations 183 8.6 Miscellaneous issues 187 8.7 Model based analysis of Affymetrix arrays 188 9 Analysis of gene sets 211 9.1 Methods for identifying enriched gene sets 213 9.2 ORA and Fisher’s exact test 217 9.3 Interpretation of results 217 9.4 Example 217 10 Pattern discovery 221 10.1 Initial considerations 222 10.2 Cluster analysis 223 10.3 Seeking patterns visually 241 10.4 Biclustering 254 11 Class prediction 263 11.1 Initial considerations 264 11.2 Linear Discriminant Analysis 269 11.3 Extensions of Fisher’s LDA 275 11.4 Penalized methods 278 11.5 Nearest neighbors 279 11.6 Recursive partitioning 280 11.7 Ensemble methods 285 11.8 Enriched ensemble classifiers 288 11.9 Neural networks 288 11.10 Support Vector Machines 289 11.11 Generalized enriched methods 291 11.12 Integration of genome information 301 12 Protein arrays 307 12.1 Introduction 307 12.2 Protein array experiments 308 12.3 Special issues with protein arrays 310 12.4 Analysis 310 12.5 Using antibody antigen arrays to measure protein concentrations 311 References 317 Index 337
£105.40
John Wiley and Sons Ltd Bioinformatics and Functional Genomics
Book SynopsisThe bestselling introduction to bioinformatics and genomics now in its third edition Widely received in its previous editions, Bioinformatics and Functional Genomics offers the most broad-based introduction to this explosive new discipline.Table of ContentsPart I Analyzing DNA, RNA, and Protein Sequences 1 Introduction 3 2 Access to Sequence Data and Related Information 19 3 Pairwise Sequence Alignment 69 4 Basic Local Alignment Search Tool (BLAST) 121 5 Advanced Database Searching 167 6 Multiple Sequence Alignment 205 7 Molecular Phylogeny and Evolution 245 Part II Genomewide Analysis of DNA, RNA, and Protein 8 DNA: The Eukaryotic Chromosome 307 9 Analysis of Next-Generation Sequence Data 377 10 Bioinformatic Approaches to Ribonucleic Acid (RNA) 433 11 Gene Expression: Microarray and RNA-seq Data Analysis 479 12 Protein Analysis and Proteomics 539 13 Protein Structure 589 14 Functional Genomics 635 Part III Genome Analysis 15 Genomes Across the Tree of Life 699 16 Completed Genomes: Viruses 755 17 Completed Genomes: Bacteria and Archaea 797 18 Eukaryotic Genomes: Fungi 847 19 Eukaryotic Genomes: From Parasites to Primates 887 20 Human Genome 957 21 Human Disease 1011 Glossary 1075 Self-Test Quiz: Solutions 1103 Author Index 1105 Subject Index 1109
£100.76
John Wiley and Sons Ltd Somatic Genome Variation
Book SynopsisWritten by an international team of experts, Somatic Genome Variation presents a timely summary of the latest understanding of somatic genome development and variation in plants, animals, and microorganisms.Table of ContentsList of Contributors xv Preface and Introduction xix Acknowledgments xxi About the Editor xxiii Part I Somatic Genome Variation in Animals and Humans 1 1 Polyploidy in Animal Development and Disease 3Jennifer L. Bandura and Norman Zielke 1.1 Introduction 3 1.2 Mechanisms Inducing Somatic Polyploidy 4 1.3 The Core Cell Cycle Machinery 8 1.4 Genomic Organization of Polyploid Cells 9 1.5 Endoreplication: An Effective Tool for Post-Mitotic Growth and Tissue Regeneration 10 1.6 Initiation of Endoreplication in Drosophila 11 1.7 Mechanisms of Endocycle Oscillations in Drosophila 15 1.8 Gene Amplification in Drosophila Follicle Cells 17 1.9 Endocycle Entry in the Trophoblast Lineage 19 1.10 Mechanisms of Endocycle Oscillations in Trophoblast Giant Cells 22 1.11 Cardiomyocytes 23 1.12 Hepatocytes 25 1.13 Megakaryocytes 28 1.14 Concluding Remarks 30 Acknowledgments 31 References 31 2 Large-Scale Programmed Genome Rearrangements in Vertebrates 45Jeramiah J. Smith 2.1 Introduction 45 2.1 Hagfish 46 2.3 Sea Lamprey 48 2.4 Zebra Finch 48 2.5 Emerging Themes and Directions 49 References 51 3 Chromosome Instability in Stem Cells 55Paola Rebuzzini, Maurizio Zuccotti, Carlo Alberto Redi and Silvia Garagna 3.1 Introduction 55 3.2 Pluripotent Stem Cells 56 3.3 Somatic Stem Cells 58 3.4 Mechanisms of Chromosomal Instability 59 3.5 Mechanisms of Chromosomal Instability in Stem Cells 63 References 63 Part II Somatic Genome Variation in Plants 75 4 Mechanisms of Induced Inheritable Genome Variation in Flax 77Christopher A. Cullis 4.1 Introduction 77 4.2 Restructuring the Flax Genome 79 4.3 Specific Genomic Changes 80 4.4 What Happens When Plastic Plants Respond to Environmental Stresses? 83 4.5 When Do the Genomic Changes Occur and Are they Adaptive? 83 4.6 Is this Genomic Response of Flax Unique? 84 4.7 Concluding Remarks 87 Acknowledgments 87 References 87 5 Environmentally Induced Genome Instability and its Inheritance 91Andrey Golubov 5.1 Introduction 91 5.2 Stress and its Effects on Genomes 92 5.3 Transgenerational Inheritance 96 5.4 Concluding Remarks 97 Acknowledgments 97 References 97 6 The Mitochondrial Genome, Genomic Shifting, and Genomic Conflict 103Gregory G. Brown 6.1 Introduction 103 6.2 Heteroplasmy and Sublimons 105 6.3 Cytoplasmic Male Sterility (CMS) in Plants 108 6.4 Mitochondrial Sublimons and CMS 109 6.5 Restorer Gene Evolution: Somatic Genetic Changes Drive Nuclear Gene Diversity? 111 6.6 Concluding Remarks 112 References 113 7 Plastid Genome Stability and Repair 119Éric Zampini, Sébastien Truche, Étienne Lepage, Samuel Tremblay]Belzile and Normand Brisson 7.1 Introduction 120 7.2 Characteristics of the Plastid Genome 121 7.3 Replication of Plastid DNA 124 7.4 Transcription in the Plastid 130 7.5 The Influence of Replication and Transcription on Plastid Genome Stability 131 7.6 Plastid Genome Stability and DNA Repair 133 7.7 Outcomes of DNA Rearrangements 145 7.8 Concluding Remarks 147 References 148 Part III Somatic Genome Variation in Microorganisms 165 8 RNA-Mediated Somatic Genome Rearrangement in Ciliates 167John R. Bracht 8.1 Introduction 168 8.2 Ciliates: Ubiquitous Eukaryotic Microorganisms with a Long Scientific History 168 8.3 Two’s Company: Nuclear Dimorphism in Ciliates 170 8.4 Paramecium: Non-Mendelian Inheritance Comes to Light 171 8.5 Tetrahymena and the Origin of the scanRNA Model 173 8.6 Small RNAs in Stylonychia and Oxytricha 175 8.7 Long Noncoding RNA Templates in Genome Rearrangement 176 8.8 Long Noncoding RNA: An Interface for Short Noncoding RNA 177 8.9 Short RNA-Mediated Heterochromatin Formation and DNA Elimination 179 8.10 Transposable Elements and the Origins of Genome Rearrangements 182 8.11 Transposons, Phase Variation, and Programmed Genome Engineering in Bacteria 185 8.12 Transposases, Noncoding RNA, and Chromatin Modifications in VDJ Recombination of Vertebrates 186 8.13 Concluding Remarks: Ubiquitous Genome Variation, Transposons, and Noncoding RNA 187 Acknowledgments 187 References 187 9 Mitotic Genome Variations in Yeast and Other Fungi 199Adrianna Skoneczna and Marek Skoneczny 9.1 Introduction 199 9.2 The Replication Process as a Possible Source of Genome Instability 200 9.3 Post-Replicative Repair (PRR) or Homologous Recombination (HR) Are Responsible for Error-Free and Error-Prone Repair of Blocking Lesions and Replication Stall-Borne Problems 219 9.4 Ploidy Maintenance and Chromosome Integrity Mechanisms 229 9.5 Concluding Remarks 234 References 235 Part IV General Genome Biology 251 10 Genome Variation in Archaeans, Bacteria, and Asexually Reproducing Eukaryotes 253Xiu-Qing Li 10.1 Introduction 254 10.2 Chromosome Number in Prokaryote Species 254 10.3 Genome Size Variation in Archaeans and Bacteria 255 10.4 Archaeal and Bacterial Genome Size Distribution 256 10.5 Genomic GC Content in Archaeans, Bacteria, Fungi, Protists, Plants, and Animals 257 10.6 Correlation between GC Content and Genome or Chromosome Size 259 10.7 Genome Size and GC-Content Variation in Primarily Asexually Reproducing Fungi 260 10.8 Variation of Gene Direction 263 10.9 Concluding Remarks 263 Acknowledgments 264 References 264 11 RNA Polyadenylation Site Regions: Highly Similar in Base Composition Pattern but Diverse in Sequence—A Combination Ensuring Similar Function but Avoiding Repetitive-Regions-Related Genomic Instability 267Xiu-Qing Li and Donglei Du 11.1 General Introduction to Gene Number, Direction, and RNA Polyadenylation 268 11.2 Base Selection at the Poly(A) Tail Starting Position 269 11.3 Most Frequent Upstream Motifs in Microorganisms, Plants, and Animals 271 11.4 Motif Frequencies in the Whole Genome 273 11.5 The Top 20 Hexamer Motifs in the Poly(A) Site Region in Humans 273 11.6 Polyadenylation Signal Motif Distribution 273 11.7 Alternative Polyadenylation 275 11.8 Base Composition of 3′UTR in Plants and Animals 276 11.9 Base Composition Comparison between 3′UTR and Whole Genome 276 11.10 Base Composition of 3′COR in Plants and Animals 277 11.11 Base Composition Pattern of the Poly(A) Site Region in Protists 278 11.12 Base Composition Pattern of the Poly(A) Site Region in Plants 280 11.13 Base Composition Pattern of the Poly(A) Site Region in Animals 280 11.14 Comparison of Poly(A) Site Region Base Composition Patterns in Plants and Animals 280 11.15 Common U-A-U-A-U Base Abundance Pattern in the Poly(A) Site Region in Fungi, Plants, and Animals 284 11.16 Difference between the Most Frequent Motifs and Seqlogo-Showed Most Frequent Bases 284 11.17 RNA Structure of the Poly(A) Site Region 286 11.18 Low Conservation in the Overall Nucleotide Sequence of the Poly(A) Site Region 286 11.19 Poly(A) Site Region Stability and Somatic Genome Variation 286 11.20 Concluding Remarks 287 Acknowledgments 288 References 288 12 Insulin Signaling Pathways in Humans and Plants 291Xiu]Qing Li and Tim Xing 12.1 Introduction 291 12.2 Ranking of the Insulin Signaling Pathway and its Key Proteins 293 12.3 Diseases Caused by Somatic Mutations of the PI3K, PTEN, and AKT Proteins in the Insulin Signaling Pathway 293 12.4 Plant Insulin and Medical Use 295 12.5 Role of the Insulin Signaling Pathway in Regulating Plant Growth 295 12.6 Concluding Remarks 295 References 296 13 Developmental Variation in the Nuclear Genome Primary Sequence 299Xiu-Qing Li 13.1 Introduction 299 13.2 Genetic Mutation, DNA Damage and Protection, and Gene Conversion in Somatic Cells 300 13.3 Programmed Large-Scale Variation in Primary DNA Sequences in Somatic Nuclear Genome 302 13.4 Generation of Antibody Genes in Animals through Somatic Genome Variation 303 13.5 Developmental Variation in Primary DNA Sequences in the Somatic Cells of Plants 303 13.6 Heritability and Stability of Developmentally Induced Variation in the Somatic Nuclear Genome in Plants 303 13.7 Concluding Remarks 304 References 305 14 Ploidy Variation of the Nuclear, Chloroplast, and Mitochondrial Genomes in Somatic Cells 309Xiu]Qing Li, Benoit Bizimungu, Guodong Zhang and Huaijun Si 14.1 Introduction 310 14.2 Nuclear Genome in Somatic Cells 311 14.3 Plastid Genome Variation in Somatic Cells 317 14.4 Mitochondrial Genome in Somatic Cells 320 14.5 Organelle Genomes in Somatic Hybrids 324 14.6 Effects of Nuclear Genome Ploidy on Organelle Genomes 325 14.7 Concluding Remarks 326 Acknowledgments 326 References 326 15 Molecular Mechanisms of Somatic Genome Variation 337Xiu-Qing Li 15.1 Introduction 338 15.2 Mutation of Genes Involved in the Cell Cycle, Cell Division, or Centromere Function 338 15.3 DNA Damage 338 15.4 Variation in Induction and Activity of Radical-Scavenging Enzymes 339 15.5 DNA Cytosine Deaminases 340 15.6 Variation in Protective Roles of Pigments against Oxidative Damage 340 15.7 RNA-Templated DNA Repair 341 15.8 Errors in DNA Repair 341 15.9 RNA-Mediated Somatic Genome Rearrangement 342 15.10 Repetitive DNA Instability 342 15.11 Extracellular DNA 343 15.12 DNA Transposition 343 15.13 Somatic Crossover and Gene Conversion 343 15.14 Molecular Heterosis 344 15.15 Genome Damage Induced by Endoplasmic Reticulum Stress 344 15.16 Telomere Degeneration 344 15.17 Concluding Remarks 344 References 345 16 Hypotheses for Interpreting Somatic Genome Variation 351Xiu-Qing Li 16.1 Introduction 352 16.2 Cell-Specific Accumulation of Somatic Genome Variation in Somatic Cells 352 16.3 Developmental Age and Genomic Network of Reproductive Cells 353 16.4 Genome Generation Cycle of Species 353 16.5 Somatic Genome Variation and Tissue-Specific Requirements during Growth or Development 354 16.6 Costs and Benefits of Somatic Genome Variation 354 16.7 Hypothesis on the Existence of a Primitive Stage in both Animals and Plants 355 16.8 Sources of Genetic Variation from in Vitro Culture Propagation 357 16.9 Hypothesis that Heterosis Is Created by Somatic Genome Variation 357 16.10 Genome Stability through Structural Similarity and Sequence Dissimilarity 358 16.11 Hypothesis Interpreting the Maternal Transmission of Organelles 358 16.12 Ability of Humans to Deal with Somatic Genome Variation and Diseases 359 16.13 Concluding Remarks 360 References 360 17 Impacts of Somatic Genome Variation on Genetic Theories and Breeding Concepts, and the Distinction between Mendelian Genetic Variation, Somagenetic Variation, and Epigenetic Variation 363Xiu]Qing Li 17.1 Introduction 364 17.2 The Term ‘Somatic Genome’ 365 17.3 Mendelian Genetic Variation, Epigenetic Variation, and Somagenetic Variation 365 17.4 What Is a Gene? 367 17.5 Breeding Criteria, Genome Cycle, Pure Lines, and Variety Stability 368 17.6 The Weismann Barrier Hypothesis and the Need for Revision 370 17.7 Implications for Species Evolution 370 17.8 Concluding Remarks 371 References 372 18 Somatic Genome Variation: What it Is and What it Means for Agriculture and Human Health 377Xiu-Qing Li 18.1 Introduction 378 18.2 Natural Attributes of Somatic Genome Variation 378 18.3 Implications of Somatic Genome Variation for Human and Animal Health 380 18.4 Implications of Somatic Genome Variation for Agriculture 385 18.5 Concluding Remarks 391 Acknowledgments 392 References 392 Index 405
£156.56
John Wiley and Sons Ltd Developmental Genomics of Ascidians
Book SynopsisThe simplicity and lack of redundancy in their regulatory genes have made ascidians one of the most useful species in studying developmental genomics. In Developmental Genomics of Ascidians, Dr.Trade Review"In his preface, the author describes Developmental Genomics of Ascidians as his “last and largest contribution to ascidian developmental biology” (p. xi). This book is indeed a major accomplishment and a great resource for the community" (The Quarterly Review of Biology 2016)Table of ContentsPREFACE ix CHAPTER 1 A BRIEF INTRODUCTION TO ASCIDIANS 1 CHAPTER 2 THE DEVELOPMENT OF TADPOLE LARVAE AND SESSILE JUVENILES 9 CHAPTER 3 GENOMICS, TRANSCRIPTOMICS, AND PROTEOMICS 19 CHAPTER 4 RESEARCH TOOLS 31 CHAPTER 5 THE FUNCTION AND REGULATION OF MATERNAL TRANSCRIPTS 41 CHAPTER 6 LARVAL TAIL MUSCLE 53 CHAPTER 7 ENDODERM 63 CHAPTER 8 EPIDERMIS 69 CHAPTER 9 NOTOCHORD 77 CHAPTER 10 THE LARVAL AND ADULT NERVOUS SYSTEMS 89 CHAPTER 11 MESENCHYME 107 CHAPTER 12 MAKING BLUEPRINT OF CHORDATE BODY: DYNAMIC ACTIVITIES OF REGULATORY GENES 113 CHAPTER 13 DEVELOPMENT OF THE JUVENILE HEART 137 CHAPTER 14 GERM-CELL LINE, GAMETES, FERTILIZATION, AND METAMORPHOSIS 145 CHAPTER 15 INNATE IMMUNE SYSTEM AND BLOOD CELLS 159 CHAPTER 16 COLONIAL ASCIDIANS: ASEXUAL REPRODUCTION AND COLONY SPECIFICITY 167 CHAPTER 17 EVOLUTIONARY DEVELOPMENTAL GENOMICS 175 INDEX 193
£107.96
John Wiley and Sons Ltd Omics in Plant Breeding
Book SynopsisComputational and high-throughput methods, such as genomics, proteomics, and transcriptomics, known collectively as -omics, have been used to study plant biology for well over a decade now. This book provides an introduction to key omicsbased methods and their application in plant breeding.Trade Review“Accessible to advanced students, researchers, and professionals, Omics in Plant Breeding will be an essential entry point into this innovative and exciting field.” (Biotechnology, Agronomy, Society and Environment, 1 October 2014) Table of ContentsList of Contributors ix Foreword xiii 1 Omics: Opening up the "Black Box" of the Phenotype 1Roberto Fritsche-Neto and Aluizio Borem The Post-Genomics Era 3 The Omics in Plant Breeding 4 Genomics, Precision Genomics, and RNA Interference 5 Transcriptomics and Proteomics 8 Metabolomics and Physiognomics 8 Phenomics 9 Bioinformatics 10 Prospects 10 References 10 2 Genomics 13Antonio Costa de Oliveira, Luciano Carlos da Maia, Daniel da Rosa Farias, and Naciele Marini The Rise of Genomics 13 DNA Sequencing 13 Development of Sequence-based Markers 18 Genome Wide Selection (GWS) 25 Structural and Comparative Genomics 27 References 28 3 Transcriptomics 33Carolina Munari Rodrigues, Valeria S. Mafra, and Marcos Antonio Machado Methods of Studying the Transcriptome 34 Applications of Transcriptomics Approaches for Crop Breeding 46 Conclusions and Future Prospects 51 Acknowledgements 51 References 51 4 Proteomics 59Ilara Gabriela F. Budzinski, Thais Regiani, Monica T. Veneziano Labate, Simone Guidetti-Gonzalez, Danielle Izilda R. da Silva, Maria Juliana Calderan Rodrigues, Janaina de Santana Borges, Ivan Miletovic Mozol, and Carlos Alberto Labate History 59 Different Methods for the Extraction of Total Proteins 60 Subcellular Proteomics 64 Post-Translational Modifications 66 Quantitative Proteomics 69 Perspectives 72 References 73 5 Metabolomics 81Valdir Diola (in memoriam), Danilo de Menezes Daloso, and Werner Camargos Antunes Introduction 81 Metabolomic and Biochemical Molecules 83 Technologies for Metabolomics 83 Metabolomic Database Analysis 86 Metabolomics Applications 89 Metabolomics-assisted Plant Breeding 91 Associative Genome Mapping and mQTL Profiles 95 Large-scale Phenotyping Using Metabolomics 97 Conclusion and Outlook 98 References 99 6 Physionomics 103Frederico Almeida de Jesus, Agustin Zsogon, and Lazaro Eustaquio Pereira Peres Introduction 103 Early Studies on Plant Physiology and the Discovery of Photosynthesis 104 Biochemical Approaches to Plant Physiology and the Discovery of Plant Hormones 104 Genetic Approaches to Plant Physiology and the Discovery of Hormone Signal Transduction Pathways 106 Alternative Genetic Models for Omics Approaches in Plant Physiology 112 "Physionomics" as an Integrator of Various Omics for Functional Studies and Plant Breeding 117 Acknowledgements 121 References 121 7 Phenomics 127Roberto Fritsche-Neto, Aluizio Borem, and Joshua N. Cobb Introduction 127 Examples of Large-scale Phenotyping 128 Important Aspects for Phenomics Implementation 134 Main Breeding Applications 141 Final Considerations 144 References 144 8 Electrophoresis, Chromatography, and Mass Spectrometry 147Thais Regiani, Ilara Gabriela F. Budzinski, Simone Guidetti-Gonzalez, Monica T. Veneziano Labate, Fernando Cotinguiba, Felipe G. Marques, Fabricio E. Moraes, and Carlos Alberto Labate Introduction 147 Two-dimensional Electrophoresis (2DE) 148 Chromatography 150 Mass Spectrometry 155 Data Analysis 161 References 164 9 Bioinformatics 167J. Miguel Ortega and Fabricio R. Santos Introduction 167 The "Omics" Megadata and Bioinformatics 167 Hardware for Modern Bioinformatics 169 Software for Genomic Sequencing 170 Software for Contig Assembling 172 Assembly Using the Graph Theory 173 New Approaches in Bioinformatics for DNA and RNA Sequencing 174 Databases, Identification of Homologous Sequences and Functional Annotation 175 Annotation of a Complete Genome 179 Computational System with Chained Tasks Manager (Workflow) 181 Applications for Studies in Plants 182 Final Considerations 183 References 184 10 Precision Genetic Engineering 187Thiago J. Nakayama, Aluizio Borem, Lucimara Chiari, Hugo Bruno Correa Molinari, and Alexandre Lima Nepomuceno Introduction 187 Zinc Finger Nucleases (ZFNs) 190 Transcription Activator-like Effector Nucleases (TALENs) 193 Meganucleases (LHEs: LAGLIDADG Homing Endonucleases) 194 Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) 195 Implications and Perspectives of the use of PGE in Plant Breeding 197 References 202 11 RNA Interference 207Francisco J.L. Aragao, Abdulrazak B. Ibrahim, and Maria Laine P. Tinoco Introduction 207 Discovery of RNAi 208 Mechanism of RNA Interference 209 Applications in Plant Breeding: Naturally Occurring Gene Silencing and Modification by Genetic Engineering 211 Resistance to Viruses 215 Host-induced Gene Silencing 218 Insect and Disease Control 218 Improving Nutritional Values 219 Secondary Metabolites 220 Perspectives 220 References 222 Index 229
£80.96
John Wiley and Sons Ltd Crumbling Genome
Book SynopsisA thought-provoking exploration of deleterious mutations in the human genome and their effects on human health and wellbeing Despite all of the elaborate mechanisms that a cell employs to handle its DNA with the utmost care, a newborn human carries about 100 new mutations, originated in their parents, about 10 of which are deleterious. A mutation replacing just one of the more than three billion nucleotides in the human genome may lead to synthesis of a dysfunctional protein, and this can be inconsistent with life or cause a tragic disease. Several percent of even young people suffer from diseases that are caused, exclusively or primarily, by pre]existing and new mutations in their genomes, including both a wide variety of genetically simple Mendelian diseases and diverse complex diseases such as birth anomalies, diabetes, and schizophrenia. Milder, but still substantial, negative effects of mutations are even more pervasive. As of now, we possess no means of reducing Table of ContentsPreface ix 1 Genotypes and Phenotypes 1 1.1 DNA is a Text 1 1.2 Genomes Small and Large 6 1.3 Genes and Intergenic Regions 7 1.4 Cells, Mitosis, and Meiosis 14 1.5 From Genotype to Phenotype 17 Further Reading 21 2 Mendelian Inheritance and Population Genetics 23 2.1 Inheritance is Discrete 23 2.2 Populations are Genetically Variable 27 2.3 Loci and Genes 33 2.4 Effects of Alleles on Phenotypes 37 2.5 Mendelian Traits and Diseases 43 Further Reading 46 3 Complex Traits and Their Inheritance 49 3.1 Complex Inheritance of Phenotypes 49 3.2 Properties of a Complex Trait 52 3.3 Complex Traits in Populations 55 3.4 Effects of Heredity and Environment on Complex Traits 60 3.5 Polymorphic Loci Behind Complex Variation 64 Further Reading 68 4 Unavoidable Mutation 71 4.1 Phenomenon of Mutation 71 4.2 Kinds of Mutations 73 4.3 Spontaneous Mutation 75 4.4 Evolution of Mutation Rates 77 4.5 Artificial Mutagenesis and Antimutagenesis 79 Further Reading 81 5 Struggle for Fidelity 83 5.1 Fidelity of DNA Replication 83 5.2 Cleaning Up After the Replisome 88 5.3 Dealing with DNA Damages 91 5.4 Harms of Broken Maintenance 96 5.5 Mechanisms of Mutation 100 Further Reading 104 6 Mutation Rates 107 6.1 Measuring Mutation Rates 107 6.2 Data on Mutation Rates 109 6.3 Guilty Older Men 112 6.4 Rates of Phenotypically Drastic Mutations 114 6.5 Mild Mutations and Mutational Pressures 118 Further Reading 121 7 Natural Selection 123 7.1 Vulnerable Adaptations and Their Evolutionary Origin 123 7.2 Two Basic Characteristics of Selection 127 7.3 Measuring Natural Selection 129 7.4 Selection at a Polymorphic Locus 132 7.5 Selection on a Quantitative Trait 135 Further Reading 138 8 Functioning DNA and Junk DNA 141 8.1 Selective Neutrality and Random Drift 141 8.2 Effective Population Size 144 8.3 Junk DNA Provides the Simplest Evidence for Evolution 144 8.4 Finding Functioning Genome Segments 145 8.5 The Genomic Rate of Deleterious Mutations 147 Further Reading 148 9 It Takes All the Running You Can Do 149 9.1 Middle Class Neighborhood for Drosophila 149 9.2 Selection Against Deleterious Alleles 153 9.3 Mutation–Selection Equilibrium 155 9.4 Inbreeding Depression 158 9.5 Dangerous Slightly Deleterious Alleles 160 Further Reading 162 10 Phenomenon of Imperfection 165 10.1 Phenotypic and Genotypic Imperfection 165 10.2 Five Evolutionary Causes of Imperfection 168 10.3 Weakly Perfect Human Genotypes and Phenotypes 171 10.4 Native, Novel, and Optimal Environments 173 10.5 Factors, Exacerbating Mutation Imperfection 175 Further Reading 176 11 Our Imperfect Fitness 177 11.1 Properties of an Allele 177 11.2 Human Derived Alleles 180 11.3 Average Imperfection of a Genotype 186 11.4 Variation Among Genotypes 190 11.5 Selection in Modern Human Populations 192 Further Reading 197 12 Our Imperfect Wellness 199 12.1 Qualitative Characteristics of Wellness 199 12.2 Quantitative Traits 206 12.3 Contributions of Heredity and Environment 208 12.4 Wellness‐impairing Alleles 211 12.5 Genetic Architecture of Wellness 215 Further Reading 217 13 Mutational Pressure on Our Species 219 13.1 Mutational Pressure on Diseases 219 13.2 Mutational Pressure on Quantitative Traits 225 13.3 Possible Increase of the Mutational Pressure 226 13.4 De Novo Mutations and Human Wellness 228 13.5 Optimistic and Pessimistic Scenarios 230 Further Reading 231 14 Ethical Issues 233 14.1 Lessons from History 233 14.2 Modern Practices 237 14.3 Humanist Ethics and the Main Concern 241 14.4 The Main Concern and Ethical Dilemmas 244 14.5 Role of Scientists 247 Further Reading 250 15 What to Do? 253 15.1 Conditionally Beneficial or Unconditionally Deleterious? 253 15.2 Mutationless Utopia: What Could It Be? 257 15.3 Mutationless Utopia: Is It Ever Going to Happen? 261 15.4 What Can I Do Without Germline Genotype Modification? 265 15.5 Prognosis 268 Further Reading 269 Index 271
£78.26
John Wiley & Sons Inc Bioinformatics and Medical Applications
Book SynopsisTable of ContentsPreface xv 1 Probabilistic Optimization of Machine Learning Algorithms for Heart Disease Prediction 1Jaspreet Kaur, Bharti Joshi and Rajashree Shedge 1.1 Introduction 2 1.1.1 Scope and Motivation 3 1.2 Literature Review 4 1.2.1 Comparative Analysis 5 1.2.2 Survey Analysis 5 1.3 Tools and Techniques 10 1.3.1 Description of Dataset 11 1.3.2 Machine Learning Algorithm 12 1.3.3 Decision Tree 14 1.3.4 Random Forest 15 1.3.5 Naive Bayes Algorithm 16 1.3.6 K Means Algorithm 18 1.3.7 Ensemble Method 18 1.3.7.1 Bagging 19 1.3.7.2 Boosting 19 1.3.7.3 Stacking 19 1.3.7.4 Majority Vote 19 1.4 Proposed Method 20 1.4.1 Experiment and Analysis 20 1.4.2 Method 22 1.5 Conclusion 25 References 26 2 Cancerous Cells Detection in Lung Organs of Human Body: IoT-Based Healthcare 4.0 Approach 29Rohit Rastogi, D.K. Chaturvedi, Sheelu Sagar, Neeti Tandon and Mukund Rastogi 2.1 Introduction 30 2.1.1 Motivation to the Study 30 2.1.1.1 Problem Statements 31 2.1.1.2 Authors’ Contributions 31 2.1.1.3 Research Manuscript Organization 31 2.1.1.4 Definitions 32 2.1.2 Computer-Aided Diagnosis System (CADe or CADx) 32 2.1.3 Sensors for the Internet of Things 32 2.1.4 Wireless and Wearable Sensors for Health Informatics 33 2.1.5 Remote Human’s Health and Activity Monitoring 33 2.1.6 Decision-Making Systems for Sensor Data 33 2.1.7 Artificial Intelligence and Machine Learning for Health Informatics 34 2.1.8 Health Sensor Data Management 34 2.1.9 Multimodal Data Fusion for Healthcare 35 2.1.10 Heterogeneous Data Fusion and Context-Aware Systems: A Context-Aware Data Fusion Approach for Health-IoT 35 2.2 Literature Review 35 2.3 Proposed Systems 37 2.3.1 Framework or Architecture of the Work 38 2.3.2 Model Steps and Parameters 38 2.3.3 Discussions 39 2.4 Experimental Results and Analysis 39 2.4.1 Tissue Characterization and Risk Stratification 39 2.4.2 Samples of Cancer Data and Analysis 40 2.5 Novelties 42 2.6 Future Scope, Limitations, and Possible Applications 42 2.7 Recommendations and Consideration 43 2.8 Conclusions 43 References 43 3 Computational Predictors of the Predominant Protein Function: SARS-CoV-2 Case 47Carlos Polanco, Manlio F. Márquez and Gilberto Vargas-Alarcón 3.1 Introduction 48 3.2 Human Coronavirus Types 49 3.3 The SARS-CoV-2 Pandemic Impact 50 3.3.1 RNA Virus vs DNA Virus 51 3.3.2 The Coronaviridae Family 51 3.3.3 The SARS-CoV-2 Structural Proteins 52 3.3.4 Protein Representations 52 3.4 Computational Predictors 53 3.4.1 Supervised Algorithms 53 3.4.2 Non-Supervised Algorithms 54 3.5 Polarity Index Method® 54 3.5.1 The PIM® Profile 54 3.5.2 Advantages 55 3.5.3 Disadvantages 55 3.5.4 SARS-CoV-2 Recognition Using PIM® Profile 55 3.6 Future Implications 59 3.7 Acknowledgments 60 References 60 4 Deep Learning in Gait Abnormality Detection: Principles and Illustrations 63Saikat Chakraborty, Sruti Sambhavi and Anup Nandy 4.1 Introduction 63 4.2 Background 65 4.2.1 LSTM 65 4.2.1.1 Vanilla LSTM 65 4.2.1.2 Bidirectional LSTM 66 4.3 Related Works 67 4.4 Methods 68 4.4.1 Data Collection and Analysis 68 4.4.2 Results and Discussion 69 4.5 Conclusion and Future Work 71 4.6 Acknowledgments 71 References 71 5 Broad Applications of Network Embeddings in Computational Biology, Genomics, Medicine, and Health 73Akanksha Jaiswar, Devender Arora, Manisha Malhotra, Abhimati Shukla and Nivedita Rai 5.1 Introduction 74 5.2 Types of Biological Networks 76 5.3 Methodologies in Network Embedding 76 5.4 Attributed and Non-Attributed Network Embedding 82 5.5 Applications of Network Embedding in Computational Biology 83 5.5.1 Understanding Genomic and Protein Interaction via Network Alignment 83 5.5.2 Pharmacogenomics 84 5.5.2.1 Drug-Target Interaction Prediction 84 5.5.2.2 Drug-Drug Interaction 84 5.5.2.3 Drug-Disease Interaction Prediction 85 5.5.2.4 Analysis of Adverse Drug Reaction 85 5.5.3 Function Prediction 86 5.5.4 Community Detection 86 5.5.5 Network Denoising 87 5.5.6 Analysis of Multi-Omics Data 87 5.6 Limitations of Network Embedding in Biology 87 5.7 Conclusion and Outlook 89 References 89 6 Heart Disease Classification Using Regional Wall Thickness by Ensemble Classifier 99Prakash J., Vinoth Kumar B. and Sandhya R. 6.1 Introduction 100 6.2 Related Study 101 6.3 Methodology 103 6.3.1 Pre-Processing 103 6.3.2 Region of Interest Extraction 104 6.3.3 Segmentation 105 6.3.4 Feature Extraction 106 6.3.5 Disease Classification 107 6.4 Implementation and Result Analysis 108 6.4.1 Dataset Description 108 6.4.2 Testbed 108 6.4.3 Discussion 108 6.4.3.1 K-Fold Cross-Validation 110 6.4.3.2 Confusion Matrix 110 6.5 Conclusion 115 References 115 7 Deep Learning for Medical Informatics and Public Health 117K. Aditya Shastry, Sanjay H. A., Lakshmi M. and Preetham N. 7.1 Introduction 118 7.2 Deep Learning Techniques in Medical Informatics and Public Health 121 7.2.1 Autoencoders 122 7.2.2 Recurrent Neural Network 123 7.2.3 Convolutional Neural Network (CNN) 124 7.2.4 Deep Boltzmann Machine 126 7.2.5 Deep Belief Network 127 7.3 Applications of Deep Learning in Medical Informatics and Public Health 128 7.3.1 The Use of DL for Cancer Diagnosis 128 7.3.2 DL in Disease Prediction and Treatment 129 7.3.3 Future Applications 133 7.4 Open Issues Concerning DL in Medical Informatics and Public Health 135 7.5 Conclusion 139 References 140 8 An Insight Into Human Pose Estimation and Its Applications 147Shambhavi Mishra, Janamejaya Channegowda and Kasina Jyothi Swaroop 8.1 Foundations of Human Pose Estimation 147 8.2 Challenges to Human Pose Estimation 149 8.2.1 Motion Blur 150 8.2.2 Indistinct Background 151 8.2.3 Occlusion or Self-Occlusion 151 8.2.4 Lighting Conditions 151 8.3 Analyzing the Dimensions 152 8.3.1 2D Human Pose Estimation 152 8.3.1.1 Single-Person Pose Estimation 153 8.3.1.2 Multi-Person Pose Estimation 153 8.3.2 3D Human Pose Estimation 153 8.4 Standard Datasets for Human Pose Estimation 154 8.4.1 Pascal VOC (Visual Object Classes) Dataset 156 8.4.2 KTH Multi-View Football Dataset I 156 8.4.3 KTH Multi-View Football Dataset II 156 8.4.4 MPII Human Pose Dataset 157 8.4.5 BBC Pose 157 8.4.6 COCO Dataset 157 8.4.7 J-HMDB Dataset 158 8.4.8 Human3.6M Dataset 158 8.4.9 DensePose 158 8.4.10 AMASS Dataset 159 8.5 Deep Learning Revolutionizing Pose Estimation 159 8.5.1 Approaches in 2D Human Pose Estimation 159 8.5.2 Approaches in 3D Human Pose Estimation 163 8.6 Application of Human Pose Estimation in Medical Domains 165 8.7 Conclusion 166 References 167 9 Brain Tumor Analysis Using Deep Learning: Sensor and IoT-Based Approach for Futuristic Healthcare 171Rohit Rastogi, D.K. Chaturvedi, Sheelu Sagar, Neeti Tandon and Akshit Rajan Rastogi 9.1 Introduction 172 9.1.1 Brain Tumor 172 9.1.2 Big Data Analytics in Health Informatics 172 9.1.3 Machine Learning in Healthcare 173 9.1.4 Sensors for Internet of Things 173 9.1.5 Challenges and Critical Issues of IoT in Healthcare 174 9.1.6 Machine Learning and Artificial Intelligence for Health Informatics 174 9.1.7 Health Sensor Data Management 175 9.1.8 Multimodal Data Fusion for Healthcare 175 9.1.9 Heterogeneous Data Fusion and Context-Aware Systems a Context-Aware Data Fusion Approach for Health-IoT 176 9.1.10 Role of Technology in Addressing the Problem of Integration of Healthcare System 176 9.2 Literature Survey 177 9.3 System Design and Methodology 179 9.3.1 System Design 179 9.3.2 CNN Architecture 180 9.3.3 Block Diagram 181 9.3.4 Algorithm(s) 181 9.3.5 Our Experimental Results, Interpretation, and Discussion 183 9.3.6 Implementation Details 183 9.3.7 Snapshots of Interfaces 184 9.3.8 Performance Evaluation 186 9.3.9 Comparison with Other Algorithms 186 9.4 Novelty in Our Work 186 9.5 Future Scope, Possible Applications, and Limitations 188 9.6 Recommendations and Consideration 188 9.7 Conclusions 188 References 189 10 Study of Emission From Medicinal Woods to Curb Threats of Pollution and Diseases: Global Healthcare Paradigm Shift in 21st Century 191Rohit Rastogi, Mamta Saxena, Devendra Kr. Chaturvedi, Sheelu Sagar, Neha Gupta, Harshit Gupta, Akshit Rajan Rastogi, Divya Sharma, Manu Bhardwaj and Pranav Sharma 10.1 Introduction 192 10.1.1 Scenario of Pollution and Need to Connect with Indian Culture 192 10.1.2 Global Pollution Scenario 192 10.1.3 Indian Crisis on Pollution and Worrying Stats 193 10.1.4 Efforts Made to Curb Pollution World Wide 194 10.1.5 Indian Ancient Vedic Sciences to Curb Pollution and Related Disease 196 10.1.6 The Yajna Science: A Boon to Human Race From Rishi-Muni 196 10.1.7 The Science of Mantra Associated With Yajna and Its Scientific Effects 197 10.1.8 Effect of Different Woods and Cow Dung Used in Yajna 197 10.1.9 Use of Sensors and IoT to Record Experimental Data 198 10.1.10 Analysis and Pattern Recognition by ML and AI 199 10.2 Literature Survey 200 10.3 The Methodology and Protocols Followed 201 10.4 Experimental Setup of an Experiment 202 10.5 Results and Discussions 202 10.5.1 Mango 202 10.5.2 Bargad 203 10.6 Applications of Yagya and Mantra Therapy in Pollution Control and Its Significance 207 10.7 Future Research Perspectives 207 10.8 Novelty of Our Research 208 10.9 Recommendations 208 10.10 Conclusions 209 References 209 11 An Economical Machine Learning Approach for Anomaly Detection in IoT Environment 215Ambika N. 11.1 Introduction 215 11.2 Literature Survey 218 11.3 Proposed Work 229 11.4 Analysis of the Work 230 11.5 Conclusion 231 References 231 12 Indian Science of Yajna and Mantra to Cure Different Diseases: An Analysis Amidst Pandemic With a Simulated Approach 235Rohit Rastogi, Mamta Saxena, Devendra Kumar Chaturvedi, Mayank Gupta, Puru Jain, Rishabh Jain, Mohit Jain, Vishal Sharma, Utkarsh Sangam, Parul Singhal and Priyanshi Garg 12.1 Introduction 236 12.1.1 Different Types of Diseases 236 12.1.1.1 Diabetes (Madhumeha) and Its Types 236 12.1.1.2 TTH and Stress 237 12.1.1.3 Anxiety 237 12.1.1.4 Hypertension 237 12.1.2 Machine Vision 237 12.1.2.1 Medical Images and Analysis 238 12.1.2.2 Machine Learning in Healthcare 238 12.1.2.3 Artificial Intelligence in Healthcare 239 12.1.3 Big Data and Internet of Things (IoT) 239 12.1.4 Machine Learning in Association with Data Science and Analytics 239 12.1.5 Yajna Science 240 12.1.6 Mantra Science 240 12.1.6.1 Positive Impact of Recital of Gayatri Mantra and OM Chanting 241 12.1.6.2 Significance of Mantra on Indian Culture and Mythology 241 12.1.7 Usefulness and Positive Aspect of Yoga Asanas and Pranayama 241 12.1.8 Effects of Yajna and Mantra on Human Health 242 12.1.9 Impact of Yajna in Reducing the Atmospheric Solution 242 12.1.10 Scientific Study on Impact of Yajna on Air Purification 243 12.1.11 Scientific Meaning of Religious and Manglik Signs 244 12.2 Literature Survey 244 12.3 Methodology 246 12.4 Results and Discussion 249 12.5 Interpretations and Analysis 250 12.6 Novelty in Our Work 258 12.7 Recommendations 259 12.8 Future Scope and Possible Applications 260 12.9 Limitations 261 12.10 Conclusions 261 12.11 Acknowledgments 262 References 262 13 Collection and Analysis of Big Data From Emerging Technologies in Healthcare 269Nagashri K., Jayalakshmi D. S. and Geetha J. 13.1 Introduction 269 13.2 Data Collection 271 13.2.1 Emerging Technologies in Healthcare and Its Applications 271 13.2.1.1 RFID 272 13.2.1.2 WSN 273 13.2.1.3 IoT 274 13.2.2 Issues and Challenges in Data Collection 277 13.2.2.1 Data Quality 277 13.2.2.2 Data Quantity 277 13.2.2.3 Data Access 278 13.2.2.4 Data Provenance 278 13.2.2.5 Security 278 13.2.2.6 Other Challenges 279 13.3 Data Analysis 280 13.3.1 Data Analysis Approaches 280 13.3.1.1 Machine Learning 280 13.3.1.2 Deep Learning 281 13.3.1.3 Natural Language Processing 281 13.3.1.4 High-Performance Computing 281 13.3.1.5 Edge-Fog Computing 282 13.3.1.6 Real-Time Analytics 282 13.3.1.7 End-User Driven Analytics 282 13.3.1.8 Knowledge-Based Analytics 283 13.3.2 Issues and Challenges in Data Analysis 283 13.3.2.1 Multi-Modal Data 283 13.3.2.2 Complex Domain Knowledge 283 13.3.2.3 Highly Competent End-Users 283 13.3.2.4 Supporting Complex Decisions 283 13.3.2.5 Privacy 284 13.3.2.6 Other Challenges 284 13.4 Research Trends 284 13.5 Conclusion 286 References 286 14 A Complete Overview of Sign Language Recognition and Translation Systems 289Kasina Jyothi Swaroop, Janamejaya Channegowda and Shambhavi Mishra 14.1 Introduction 289 14.2 Sign Language Recognition 290 14.2.1 Fundamentals of Sign Language Recognition 290 14.2.2 Requirements for the Sign Language Recognition 292 14.3 Dataset Creation 293 14.3.1 American Sign Language 293 14.3.2 German Sign Language 296 14.3.3 Arabic Sign Language 297 14.3.4 Indian Sign Language 298 14.4 Hardware Employed for Sign Language Recognition 299 14.4.1 Glove/Sensor-Based Systems 299 14.4.2 Microsoft Kinect–Based Systems 300 14.5 Computer Vision–Based Sign Language Recognition and Translation Systems 302 14.5.1 Image Processing Techniques for Sign Language Recognition 302 14.5.2 Deep Learning Methods for Sign Language Recognition 304 14.5.3 Pose Estimation Application to Sign Language Recognition 305 14.5.4 Temporal Information in Sign Language Recognition and Translation 306 14.6 Sign Language Translation System—A Brief Overview 307 14.7 Conclusion 309 References 310 Index 315
£169.16
John Wiley & Sons Inc Computational Intelligence and Healthcare
Book SynopsisTable of ContentsPreface xv Part I: Introduction 1 1 Machine Learning and Big Data: An Approach Toward Better Healthcare Services 3Nahid Sami and Asfia Aziz 1.1 Introduction 3 1.2 Machine Learning in Healthcare 4 1.3 Machine Learning Algorithms 6 1.3.1 Supervised Learning 6 1.3.2 Unsupervised Learning 7 1.3.3 Semi-Supervised Learning 7 1.3.4 Reinforcement Learning 8 1.3.5 Deep Learning 8 1.4 Big Data in Healthcare 8 1.5 Application of Big Data in Healthcare 9 1.5.1 Electronic Health Records 9 1.5.2 Helping in Diagnostics 9 1.5.3 Preventive Medicine 10 1.5.4 Precision Medicine 10 1.5.5 Medical Research 10 1.5.6 Cost Reduction 10 1.5.7 Population Health 10 1.5.8 Telemedicine 10 1.5.9 Equipment Maintenance 11 1.5.10 Improved Operational Efficiency 11 1.5.11 Outbreak Prediction 11 1.6 Challenges for Big Data 11 1.7 Conclusion 11 References 12 Part II: Medical Data Processing and Analysis 15 2 Thoracic Image Analysis Using Deep Learning 17Rakhi Wajgi, Jitendra V. Tembhurne and Dipak Wajgi 2.1 Introduction 18 2.2 Broad Overview of Research 19 2.2.1 Challenges 19 2.2.2 Performance Measuring Parameters 21 2.2.3 Availability of Datasets 21 2.3 Existing Models 23 2.4 Comparison of Existing Models 30 2.5 Summary 38 2.6 Conclusion and Future Scope 38 References 39 3 Feature Selection and Machine Learning Models for High-Dimensional Data: State-of-the-Art 43G. Manikandan and S. Abirami 3.1 Introduction 43 3.1.1 Motivation of the Dimensionality Reduction 45 3.1.2 Feature Selection and Feature Extraction 46 3.1.3 Objectives of the Feature Selection 47 3.1.4 Feature Selection Process 47 3.2 Types of Feature Selection 48 3.2.1 Filter Methods 49 3.2.1.1 Correlation-Based Feature Selection 49 3.2.1.2 The Fast Correlation-Based Filter 50 3.2.1.3 The INTERACT Algorithm 51 3.2.1.4 ReliefF 51 3.2.1.5 Minimum Redundancy Maximum Relevance 52 3.2.2 Wrapper Methods 52 3.2.3 Embedded Methods 53 3.2.4 Hybrid Methods 54 3.3 Machine Learning and Deep Learning Models 55 3.3.1 Restricted Boltzmann Machine 55 3.3.2 Autoencoder 56 3.3.3 Convolutional Neural Networks 57 3.3.4 Recurrent Neural Network 58 3.4 Real-World Applications and Scenario of Feature Selection 58 3.4.1 Microarray 58 3.4.2 Intrusion Detection 59 3.4.3 Text Categorization 59 3.5 Conclusion 59 References 60 4 A Smart Web Application for Symptom-Based Disease Detection and Prediction Using State-of-the-Art ML and ANN Models 65Parvej Reja Saleh and Eeshankur Saikia 4.1 Introduction 65 4.2 Literature Review 68 4.3 Dataset, EDA, and Data Processing 69 4.4 Machine Learning Algorithms 72 4.4.1 Multinomial Naïve Bayes Classifier 72 4.4.2 Support Vector Machine Classifier 72 4.4.3 Random Forest Classifier 73 4.4.4 K-Nearest Neighbor Classifier 74 4.4.5 Decision Tree Classifier 74 4.4.6 Logistic Regression Classifier 75 4.4.7 Multilayer Perceptron Classifier 76 4.5 Work Architecture 77 4.6 Conclusion 78 References 79 5 Classification of Heart Sound Signals Using Time-Frequency Image Texture Features 81Sujata Vyas, Mukesh D. Patil and Gajanan K. Birajdar 5.1 Introduction 81 5.1.1 Motivation 82 5.2 Related Work 83 5.3 Theoretical Background 84 5.3.1 Pre-Processing Techniques 84 5.3.2 Spectrogram Generation 85 5.3.2 Feature Extraction 88 5.3.4 Feature Selection 90 5.3.5 Support Vector Machine 91 5.4 Proposed Algorithm 91 5.5 Experimental Results 92 5.5.1 Database 92 5.5.2 Evaluation Metrics 94 5.5.3 Confusion Matrix 94 5.5.4 Results and Discussions 94 5.6 Conclusion 96 References 99 6 Improving Multi-Label Classification in Prototype Selection Scenario 103Himanshu Suyal and Avtar Singh 6.1 Introduction 103 6.2 Related Work 105 6.3 Methodology 106 6.3.1 Experiments and Evaluation 108 6.4 Performance Evaluation 108 6.5 Experiment Data Set 109 6.6 Experiment Results 110 6.7 Conclusion 117 References 117 7 A Machine Learning–Based Intelligent Computational Framework for the Prediction of Diabetes Disease 121Maqsood Hayat, Yar Muhammad and Muhammad Tahir 7.1 Introduction 121 7.2 Materials and Methods 123 7.2.1 Dataset 123 7.2.2 Proposed Framework for Diabetes System 124 7.2.3 Pre-Processing of Data 124 7.3 Machine Learning Classification Hypotheses 124 7.3.1 K-Nearest Neighbor 124 7.3.2 Decision Tree 125 7.3.3 Random Forest 126 7.3.4 Logistic Regression 126 7.3.5 Naïve Bayes 126 7.3.6 Support Vector Machine 126 7.3.7 Adaptive Boosting 126 7.3.8 Extra-Tree Classifier 127 7.4 Classifier Validation Method 127 7.4.1 K-Fold Cross-Validation Technique 127 7.5 Performance Evaluation Metrics 127 7.6 Results and Discussion 129 7.6.1 Performance of All Classifiers Using 5-Fold CV Method 129 7.6.2 Performance of All Classifiers Using the 7-Fold Cross-Validation Method 131 7.6.3 Performance of All Classifiers Using 10-Fold CV Method 133 7.7 Conclusion 137 References 137 8 Hyperparameter Tuning of Ensemble Classifiers Using Grid Search and Random Search for Prediction of Heart Disease 139Dhilsath Fathima M. and S. Justin Samuel 8.1 Introduction 140 8.2 Related Work 140 8.3 Proposed Method 142 8.3.1 Dataset Description 143 8.3.2 Ensemble Learners for Classification Modeling 144 8.3.2.1 Bagging Ensemble Learners 145 8.3.2.2 Boosting Ensemble Learner 147 8.3.3 Hyperparameter Tuning of Ensemble Learners 151 8.3.3.1 Grid Search Algorithm 151 8.3.3.2 Random Search Algorithm 152 8.4 Experimental Outcomes and Analyses 153 8.4.1 Characteristics of UCI Heart Disease Dataset 153 8.4.2 Experimental Result of Ensemble Learners and Performance Comparison 154 8.4.3 Analysis of Experimental Result 154 8.5 Conclusion 157 References 157 9 Computational Intelligence and Healthcare Informatics Part III—Recent Development and Advanced Methodologies 159Sankar Pariserum Perumal, Ganapathy Sannasi, Santhosh Kumar S.V.N. and Kannan Arputharaj 9.1 Introduction: Simulation in Healthcare 160 9.2 Need for a Healthcare Simulation Process 160 9.3 Types of Healthcare Simulations 161 9.4 AI in Healthcare Simulation 163 9.4.1 Machine Learning Models in Healthcare Simulation 163 9.4.1.1 Machine Learning Model for Post-Surgical Risk Prediction 163 9.4.2 Deep Learning Models in Healthcare Simulation 169 9.4.2.1 Bi-LSTM–Based Surgical Participant Prediction Model 170 9.5 Conclusion 174 References 174 10 Wolfram’s Cellular Automata Model in Health Informatics 179Sutapa Sarkar and Mousumi Saha 10.1 Introduction 179 10.2 Cellular Automata 181 10.3 Application of Cellular Automata in Health Science 183 10.4 Cellular Automata in Health Informatics 184 10.5 Health Informatics–Deep Learning–Cellular Automata 190 10.6 Conclusion 191 References 191 Part III: Machine Learning and COVID Prospective 193 11 COVID-19: Classification of Countries for Analysis and Prediction of Global Novel Corona Virus Infections Disease Using Data Mining Techniques 195Sachin Kamley, Shailesh Jaloree, R.S. Thakur and Kapil Saxena 11.1 Introduction 195 11.2 Literature Review 196 11.3 Data Pre-Processing 197 11.4 Proposed Methodologies 198 11.4.1 Simple Linear Regression 198 11.4.2 Association Rule Mining 202 11.4.3 Back Propagation Neural Network 203 11.5 Experimental Results 204 11.6 Conclusion and Future Scopes 211 References 212 12 Sentiment Analysis on Social Media for Emotional Prediction During COVID-19 Pandemic Using Efficient Machine Learning Approach 215Sivanantham Kalimuthu 12.1 Introduction 215 12.2 Literature Review 218 12.3 System Design 222 12.3.1 Extracting Feature With WMAR 224 12.4 Result and Discussion 229 12.5 Conclusion 232 References 232 13 Primary Healthcare Model for Remote Area Using Self-Organizing Map Network 235Sayan Das and Jaya Sil 13.1 Introduction 236 13.2 Background Details and Literature Review 239 13.2.1 Fuzzy Set 239 13.2.2 Self-Organizing Mapping 239 13.3 Methodology 240 13.3.1 Severity_Factor of Patient 244 13.3.2 Clustering by Self-Organizing Mapping 249 13.4 Results and Discussion 250 13.5 Conclusion 252 References 252 14 Face Mask Detection in Real-Time Video Stream Using Deep Learning 255Alok Negi and Krishan Kumar 14.1 Introduction 256 14.2 Related Work 257 14.3 Proposed Work 258 14.3.1 Dataset Description 258 14.3.2 Data Pre-Processing and Augmentation 258 14.3.3 VGG19 Architecture and Implementation 259 14.3.4 Face Mask Detection From Real-Time Video Stream 261 14.4 Results and Evaluation 262 14.5 Conclusion 267 References 267 15 A Computational Intelligence Approach for Skin Disease Identification Using Machine/Deep Learning Algorithms 269Swathi Jamjala Narayanan, Pranav Raj Jaiswal, Ariyan Chowdhury, Amitha Maria Joseph and Saurabh Ambar 15.1 Introduction 270 15.2 Research Problem Statements 274 15.3 Dataset Description 274 15.4 Machine Learning Technique Used for Skin Disease Identification 276 15.4.1 Logistic Regression 277 15.4.1.1 Logistic Regression Assumption 277 15.4.1.2 Logistic Sigmoid Function 277 15.4.1.3 Cost Function and Gradient Descent 278 15.4.2 SVM 279 15.4.3 Recurrent Neural Networks 281 15.4.4 Decision Tree Classification Algorithm 283 15.4.5 CNN 286 15.4.6 Random Forest 288 15.5 Result and Analysis 290 15.6 Conclusion 291 References 291 16 Asymptotic Patients’ Healthcare Monitoring and Identification of Health Ailments in Post COVID-19 Scenario 297Pushan K.R. Dutta, Akshay Vinayak and Simran Kumari 16.1 Introduction 298 16.1.1 Motivation 298 16.1.2 Contributions 299 16.1.3 Paper Organization 299 16.1.4 System Model Problem Formulation 299 16.1.5 Proposed Methodology 300 16.2 Material Properties and Design Specifications 301 16.2.1 Hardware Components 301 16.2.1.1 Microcontroller 301 16.2.1.2 ESP8266 Wi-Fi Shield 301 16.2.2 Sensors 301 16.2.2.1 Temperature Sensor (LM 35) 301 16.2.2.2 ECG Sensor (AD8232) 301 16.2.2.3 Pulse Sensor 301 16.2.2.4 GPS Module (NEO 6M V2) 302 16.2.2.5 Gyroscope (GY-521) 302 16.2.3 Software Components 302 16.2.3.1 Arduino Software 302 16.2.3.2 MySQL Database 302 16.2.3.3 Wireless Communication 302 16.3 Experimental Methods and Materials 303 16.3.1 Simulation Environment 303 16.3.1.1 System Hardware 303 16.3.1.2 Connection and Circuitry 304 16.3.1.3 Protocols Used 306 16.3.1.4 Libraries Used 307 16.4 Simulation Results 307 16.5 Conclusion 310 16.6 Abbreviations and Acronyms 310 References 311 17 COVID-19 Detection System Using Cellular Automata–Based Segmentation Techniques 313Rupashri Barik, M. Nazma B. J. Naskar and Sarbajyoti Mallik 17.1 Introduction 313 17.2 Literature Survey 314 17.2.1 Cellular Automata 315 17.2.2 Image Segmentation 316 17.2.3 Deep Learning Techniques 316 17.3 Proposed Methodology 317 17.4 Results and Discussion 320 17.5 Conclusion 322 References 322 18 Interesting Patterns From COVID-19 Dataset Using Graph-Based Statistical Analysis for Preventive Measures 325Abhilash C. B. and Kavi Mahesh 18.1 Introduction 326 18.2 Methods 326 18.2.1 Data 326 18.3 GSA Model: Graph-Based Statistical Analysis 327 18.4 Graph-Based Analysis 329 18.4.1 Modeling Your Data as a Graph 329 18.4.2 RDF for Knowledge Graph 331 18.4.3 Knowledge Graph Representation 331 18.4.4 RDF Triple for KaTrace 333 18.4.5 Cipher Query Operation on Knowledge Graph 335 18.4.5.1 Inter-District Travel 335 18.4.5.2 Patient 653 Spread Analysis 336 18.4.5.3 Spread Analysis Using Parent-Child Relationships 337 18.4.5.4 Delhi Congregation Attended the Patient’s Analysis 339 18.5 Machine Learning Techniques 339 18.5.1 Apriori Algorithm 339 18.5.2 Decision Tree Classifier 341 18.5.3 System Generated Facts on Pandas 343 18.5.4 Time Series Model 345 18.6 Exploratory Data Analysis 346 18.6.1 Statistical Inference 347 18.7 Conclusion 356 18.8 Limitations 356 Acknowledgments 356 Abbreviations 357 References 357 Part IV: Prospective of Computational Intelligence in Healthcare 359 19 Conceptualizing Tomorrow’s Healthcare Through Digitization 361Riddhi Chatterjee, Ratula Ray, Satya Ranjan Dash and Om Prakash Jena 19.1 Introduction 361 19.2 Importance of IoMT in Healthcare 362 19.3 Case Study I: An Integrated Telemedicine Platform in Wake of the COVID-19 Crisis 363 19.3.1 Introduction to the Case Study 363 19.3.2 Merits 363 19.3.3 Proposed Design 363 19.3.3.1 Homecare 363 19.3.3.2 Healthcare Provider 365 19.3.3.3 Community 367 19.4 Case Study II: A Smart Sleep Detection System to Track the Sleeping Pattern in Patients Suffering From Sleep Apnea 371 19.4.1 Introduction to the Case Study 371 19.4.2 Proposed Design 373 19.5 Future of Smart Healthcare 375 19.6 Conclusion 375 References 375 20 Domain Adaptation of Parts of Speech Annotators in Hindi Biomedical Corpus: An NLP Approach 377Pitambar Behera and Om Prakash Jena 20.1 Introduction 377 20.1.1 COVID-19 Pandemic Situation 378 20.1.2 Salient Characteristics of Biomedical Corpus 378 20.2 Review of Related Literature 379 20.2.1 Biomedical NLP Research 379 20.2.2 Domain Adaptation 379 20.2.3 POS Tagging in Hindi 380 20.3 Scope and Objectives 380 20.3.1 Research Questions 380 20.3.2 Research Problem 380 20.3.3 Objectives 381 20.4 Methodological Design 381 20.4.1 Method of Data Collection 381 20.4.2 Method of Data Annotation 381 20.4.2.1 The BIS Tagset 381 20.4.2.2 ILCI Semi-Automated Annotation Tool 382 20.4.2.3 IA Agreement 383 20.4.3 Method of Data Analysis 383 20.4.3.1 The Theory of Support Vector Machines 384 20.4.3.2 Experimental Setup 384 20.5 Evaluation 385 20.5.1 Error Analysis 386 20.5.2 Fleiss’ Kappa 388 20.6 Issues 388 20.7 Conclusion and Future Work 388 Acknowledgements 389 References 389 21 Application of Natural Language Processing in Healthcare 393Khushi Roy, Subhra Debdas, Sayantan Kundu, Shalini Chouhan, Shivangi Mohanty and Biswarup Biswas 21.1 Introduction 393 21.2 Evolution of Natural Language Processing 395 21.3 Outline of NLP in Medical Management 396 21.4 Levels of Natural Language Processing in Healthcare 397 21.5 Opportunities and Challenges From a Clinical Perspective 399 21.5.1 Application of Natural Language Processing in the Field of Medical Health Records 399 21.5.2 Using Natural Language Processing for Large-Sample Clinical Research 400 21.6 Openings and Difficulties From a Natural Language Processing Point of View 401 21.6.1 Methods for Developing Shareable Data 401 21.6.2 Intrinsic Evaluation and Representation Levels 402 21.6.3 Beyond Electronic Health Record Data 403 21.7 Actionable Guidance and Directions for the Future 403 21.8 Conclusion 406 References 406 Index 409
£168.26
John Wiley and Sons Ltd The Ecological Genomics of Fungi
Book SynopsisEdited and written by leading researchers from around the world, The Ecological Genomics of Fungi covers a broad diversity of fungal systems and provides unique insight into the functions of those fungi in various ecosystems, from soil, to plant, to human.Trade Review“I think the volume may succeed in its ambition to serve as a catalyst for further studies by showing researchers venturing into ecological genomics and those already in genomics the width of the field. This may, in turn, further more integrative studies that will benefit our understanding of fungi.” (The Quarterly Review of Biology, 1 October 2015) Table of ContentsContributors vii Preface xiii Section 1 Sequencing Fungal Genomes 1 1 A Changing Landscape of Fungal Genomics 3 Igor V. Grigoriev 2 Repeated Elements in Filamentous Fungi with a Focus on Wood-Decay Fungi 21 Claude Murat, Thibaut Payen, Denis Petitpierre, and Jessy Labbé Section 2 Saprotrophic Fungi 41 3 Wood Decay 43 Dan Cullen 4 Aspergilli and Biomass-Degrading Fungi 63 Isabelle Benoit, Ronald P. de Vries, Scott E. Baker, and Sue A. Karagiosis 5 Ecological Genomics of Trichoderma 89 Irina S. Druzhinina and Christian P. Kubicek Section 3 Plant-Interacting Fungi 117 6 Dothideomycetes: Plant Pathogens, Saprobes, and Extremophiles 119 Stephen B. Goodwin 7 Biotrophic Fungi (Powdery Mildews, Rusts, and Smuts) 149 Sébastien Duplessis, Pietro D. Spanu, and Jan Schirawski 8 The Mycorrhizal Symbiosis Genomics 169 Francis Martin and Annegret Kohler 9 Lichen Genomics: Prospects and Progress 191 Martin Grube, Gabriele Berg, ólafur S. Andrésson, Oddur Vilhelmsson, Paul S. Dyer, and Vivian P.W. Miao Section 4 Animal-Interacting Fungi 213 10 Ecogenomics of Human and Animal Basidiomycetous Yeast Pathogens 215 Sheng Sun, Ferry Hagen, Jun Xu, Tom Dawson, Joseph Heitman, James Kronstad, Charles Saunders, and Teun Boekhout 11 Genomics of Entomopathogenic Fungi 243 Chengshu Wang and Raymond J. St. Leger 12 Ecological Genomics of the Microsporidia 261 Nicolas Corradi and Patrick J. Keeling Section 5 Metagenomics and Biogeography of Fungi 279 13 Metagenomics for Study of Fungal Ecology 281 Björn D. Lindahl and Cheryl R. Kuske 14 Metatranscriptomics of Soil Eukaryotic Communities 305 Laurence Fraissinet-Tachet, Roland Marmeisse, Lucie Zinger, and Patricia Luis 15 Fungi in Deep-Sea Environments and Metagenomics 325 Stéphane Mahé, Vanessa Rédou, Thomas Le Calvez, Philippe Vandenkoornhuyse, and Gaëtan Burgaud 16 The Biodiversity, Ecology, and Biogeography of Ascomycetous Yeasts 355 Marc-André Lachance Index 371
£159.26
John Wiley and Sons Ltd Plant Genes Genomes and Genetics
Book SynopsisPlant Genes, Genomes and Genetics provides a comprehensive treatment of all aspects of plant gene expression. Unique in explaining the subject from a plant perspective, it highlights the importance of key processes, many first discovered in plants, that impact how plants develop and interact with the environment.Table of ContentsAcknowledgements xi Introduction xiii About the Companion Website xix PART I: PLANT GENOMES AND GENES Chapter 1 Plant genetic material 3 1.1 DNA is the genetic material of all living organisms, including plants 3 1.2 The plant cell contains three independent genomes 8 1.3 A gene is a complete set of instructions for building an RNA molecule 10 1.4 Genes include coding sequences and regulatory sequences 11 1.5 Nuclear genome size in plants is variable but the numbers of protein-coding, non-transposable element genes are roughly the same 12 1.6 Genomic DNA is packaged in chromosomes 15 1.7 Summary 15 1.8 Problems 15 References 16 Chapter 2 The shifting genomic landscape 17 2.1 The genomes of individual plants can differ in many ways 17 2.2 Differences in sequences between plants provide clues about gene function 20 2.3 SNPs and lengthmutations in simple sequence repeats are useful tools for genome mapping and marker assisted selection 22 2.4 Genome size and chromosome number are variable 28 2.5 Segments of DNA are often duplicated and can recombine 30 2.6 Some genes are copied nearby in the genome 31 2.7 Whole genome duplications are common in plants 34 2.8 Whole genome duplication has many effects on the genome and on gene function 37 2.9 Summary 41 2.10 Problems 42 Further reading 42 References 42 Chapter 3 Transposable elements 45 3.1 Transposable elements are common in genomes of all organisms 45 3.2 Retrotransposons are mainly responsible for increases in genome size 46 3.3 DNA transposons create small mutations when they insert and excise 52 3.4 Transposable elements move genes and change their regulation 57 3.5 How are transposable elements controlled? 60 3.6 Summary 60 3.7 Problems 61 References 61 Chapter 4 Chromatin, centromeres and telomeres 63 4.1 Chromosomes are made up of chromatin, a complex of DNA and protein 63 4.2 Telomeres make up the ends of chromosomes 67 4.3 The chromosome middles–centromeres 71 4.4 Summary 77 4.5 Problems 77 Further reading 77 References 77 Chapter 5 Genomes of organelles 79 5.1 Plastids and mitochondria are descendants of free-living bacteria 79 5.2 Organellar genes have been transferred to the nuclear genome 80 5.3 Organellar genes sometimes include introns 82 5.4 Organellar mRNA is often edited 82 5.5 Mitochondrial genomes contain fewer genes than chloroplasts 84 5.6 Plant mitochondrial genomes are large and undergo frequent recombination 87 5.7 All plastid genomes in a cell are identical 91 5.8 Plastid genomes are similar among land plants but contain some structural rearrangements 93 5.9 Summary 95 5.10 Problems 95 Further reading 95 References 95 PART II: TRANSCRIBING PLANT GENES Chapter 6 RNA 99 6.1 RNA links components of the Central Dogma 99 6.2 Structure provides RNA with unique properties 102 6.3 RNA has multiple regulatory activities 105 6.4 Summary 108 6.5 Problems 108 References 109 Chapter 7 The plant RNA polymerases 111 7.1 Transcription makes RNA from DNA 111 7.2 Varying numbers of RNA polymerases in the different kingdoms 112 7.3 RNA polymerase I transcribes rRNAs 114 7.4 RNA polymerase III recruitment to upstream and internal promoters 116 7.5 Plant-specific RNP-IV and RNP-V participate in transcriptional gene silencing 117 7.6 Organelles have their own set of RNA polymerases 117 7.7 Summary 118 7.8 Problems 118 References 118 Chapter 8 Making mRNAs – Control of transcription by RNA polymerase II 121 8.1 RNA polymerase II transcribes protein-coding genes 121 8.2 The structure of RNA polymerase II reveals how it functions 121 8.3 The core promoter 123 8.4 Initiation of transcription 125 8.5 The mediator complex 127 8.6 Transcription elongation: the role of RNP-II phosphorylation 128 8.7 RNP-II pausing and termination 129 8.8 Transcription re-initiation 130 8.9 Summary 130 8.10 Problems 130 References 130 Chapter 9 Transcription factors interpret cis-regulatory information 133 9.1 Information on when, where and how much a gene is expressed is codified by the gene’s regulatory regions 133 9.2 Identifying regulatory regions requires the use of reporter genes 134 9.3 Gene regulatory regions have a modular structure 135 9.4 Enhancers: Cis-regulatory elements or modules that function at a distance 137 9.5 Transcription factors interpret the gene regulatory code 138 9.6 Transcription factors can be classified in families 138 9.7 How transcription factors bind DNA 139 9.8 Modular structure of transcription factors 143 9.9 Organization of transcription factors into gene regulatory grids and networks 146 9.10 Summary 146 9.11 Problems 146 More challenging problems 147 References 147 Chapter 10 Control of transcription factor activity 149 10.1 Transcription factor phosphorylation 149 10.2 Protein–protein interactions 151 10.3 Preventing transcription factors from access to the nucleus 155 10.4 Movement of transcription factors between cells 156 10.5 Summary 158 10.6 Problems 158 References 158 Chapter 11 Small RNAs 161 11.1 The phenomenon of cosuppression or gene silencing 161 11.2 Discovery of small RNAs 162 11.3 Pathways for miRNA formation and function 163 11.4 Plant siRNAs originate from different types of double-stranded RNAs 166 11.5 Intercellular and systemic movement of small RNAs 168 11.6 Role of miRNAs in plant physiology and development 170 11.7 Summary 171 11.8 Problems 171 References 172 Chapter 12 Chromatin and gene expression 173 12.1 Packing long DNA molecules in a small space: the function of chromatin 173 12.2 Heterochromatin and euchromatin 173 12.3 Histone modifications 174 12.4 Histone modifications affect gene expression 175 12.5 Introducing and removing histone marks: writers and erasers 175 12.6 ‘Readers’ recognize histone modifications 177 12.7 Nucleosome positioning 177 12.8 DNA methylation 178 12.9 RNA-directed DNA methylation 179 12.10 Control of flowering by histone modifications 180 12.11 Summary 181 12.12 Problems 181 References 181 PART III: FROM RNA TO PROTEINS Chapter 13 RNA processing and transport 185 13.1 RNA processing can be thought of as steps 185 13.2 RNA capping provides a distinctive 5’ end to mRNAs 185 13.3 Transcription termination consists of mRNA 3’-end formation and polyadenylation 189 13.4 RNA splicing is another major source of genetic variation 192 13.5 Export of mRNA from the nucleus is a gateway for regulating which mRNAs actually get translated 194 13.6 Summary 196 13.7 Problems 196 References 196 Chapter 14 Fate of RNA 199 14.1 Regulation of RNA continues upon export from nucleus 199 14.2 Mechanisms for RNA turnover 199 14.3 RNA surveillance mechanisms 201 14.4 RNA sorting 202 14.5 RNA movement 203 14.6 Summary 204 14.7 Problems 204 Further reading 205 References 205 Chapter 15 Translation of RNA 207 15.1 Translation: a key aspect of gene expression 207 15.2 Initiation 209 15.3 Elongation 209 15.4 Termination 210 15.5 Tools for studying the regulation of translation 211 15.6 Specific translational control mechanisms 211 15.7 Summary 213 15.8 Problems 214 Further reading 214 References 214 Chapter 16 Protein folding and transport 215 16.1 The pathway to a protein’s function is a complicated matter 215 16.2 Protein folding and assembly 215 16.3 Protein targeting 218 16.4 Co-translational targeting 218 16.5 Post-translational targeting 219 16.6 Post-translational modifications regulating function 220 16.7 Summary 222 16.8 Problems 223 Further reading 223 References 224 Chapter 17 Protein degradation 225 17.1 Two sides of gene expression–synthesis and degradation 225 17.2 Autophagy, senescence and programmed cell death 225 17.3 Protein-tagging mechanisms 226 17.4 The ubiquitin proteasome system rivals gene transcription 228 17.5 Summary 231 17.6 Problems 231 Further reading 231 Reference 231 Index 233
£95.90
Cambridge University Press Computational Thinking for Life Scientists
Book SynopsisComputational thinking is increasingly gaining importance in modern biology, due to the unprecedented scale at which data is nowadays produced. Bridging the cultural gap between the biological and computational sciences, this book serves as an accessible introduction to computational concepts for students in the life sciences. It focuses on teaching algorithmic and logical thinking, rather than just the use of existing bioinformatics tools or programming. Topics are presented from a biological point of view, to demonstrate how computational approaches can be used to solve problems in biology such as biological image processing, regulatory networks, and sequence analysis. The book contains a range of pedagogical features to aid understanding, including real-world examples, in-text exercises, end-of-chapter problems, colour-coded Python code, and ''code explained'' boxes. User-friendly throughout, Computational Thinking for Life Scientists promotes the thinking skills and self-efficacy rTrade Review'An excellent and very gentle introduction to bioinformatics for biologists. In contrast to books that focus on algorithms and ignore programming or focus on programming without explaining algorithms, this book is a perfect blend of both algorithms and programming!' Pavel Pevzner, Ronald R. Taylor Chair and Distinguished Professor of Computer Science, University of California at San Diego'The ability to extract quantitative information from data is an essential skill for the modern biologist. In order to maximize the benefit of programming, use of existing computational tools and effective collaboration with computational scientists, biologists must be able to 'think computationally' by gaining a more algorithmic and logical thinking. In their book, Benny Chor and Amir Rubinstein introduce fundamental computational concepts to life sciences students. Each chapter covers a distinct computational idea motivated by a concrete biological challenge. Questions embedded throughout each chapter and code examples provide hands-on practice. Similarly to the way in which chemistry is perceived as being essential to the biology curriculum, computational thinking should also be considered a part of the modern biologist's basic training. This excellent book is essential reading for undergraduate life sciences students.' Assaf Zaritsky, Ben-Gurion University of the Negev, IsraelTable of ContentsIntroduction; Part I. Programming in Python: 1. Crash introduction to python; 2. Efficiency matters – gentle intro to complexity; Part II. Sequences: 3. Sets dictionaries and hashing; 4. Regular expressions and biological patterns; Part III. Networks: 5. Basic notions in graph theory; 6. Shortest paths and breadth first search; 7. Simulation of regulatory networks; Part IV. Images: 8. Digital images representation; 9. Image processing; Part V. Limitations of Computing: 10. Mission impossible; 11. Mission infeasible; Index.
£28.49
John Wiley and Sons Ltd Principles of Genome Analysis and Genomics
Book SynopsisWith the first draft of the human genome project in the public domain and full analyses of model genomes now available, the subject matter of ''Principles of Genome Analysis and Genomics'' is even ''hotter'' now than when the first two editions were published in 1995 and 1998. In the new edition of this very practical guide to the different techniques and theory behind genomes and genome analysis, Sandy Primrose and new author Richard Twyman provide a fresh look at this topic. In the light of recent exciting advancements in the field, the authors have completely revised and rewritten many parts of the new edition with the addition of five new chapters. Aimed at upper level students, it is essential that in this extremely fast moving topic area the text is up to date and relevant. Completely revised new edition of an established textbook. Features new chapters and examples from exciting new research in genomics, including the human genome project. ExcelTrade Review"...an excellent distillation of current knowledge...The book is clearly written, well presented, and feels good. Recommended." Neil Stoker, Royal Veterninary College, London, Microbiology Today, Vol 30, November 2003 "There is no doubt that this book is a very useful source of information, for students and teachers alike. In spite of its dense text, it makes good reading and will help to reduce the general bewilderment induced by the rapid pace of technological and conceptual innovation in biology." Leon Otten, Plant Molecular Biology Institute, Plant Science, 2003. Principles of Genome Analysis and Genomics, 3rd edition, is "very good indeed and deserves to be a widely popular resource for newcomers to genome analysis." J.Armour, University of Nottingham, Heredity, June 2004 Table of ContentsPreface. Abbreviations. 1. Setting The Scene: The New Science Of Genomics. 2. The Organization And Structure Of Genomes. 3. Subdividing The Genome. 4. Assembling A Physical Map Of The Genome. 5. Sequencing Methods And Strategies. 6. Genome Annotation And Bioinformatics. 7. Comparative Genomics. 8. Protein Structural Genomics. 9. Global Expression Profiling. 10. Comprehensive Mutant Libraries. 11. Mapping Protein Interactions. 12. Applications Of Genome Analysis And Genomics. References. Index
£60.26
John Wiley and Sons Ltd Microarray Gene Expression Data Analysis
Book SynopsisThis guide covers aspects of designing microarray experiments and analysing the data generated, including information on some of the tools that are available from non-commercial sources. Concepts and principles underpinning gene expression analysis are emphasised and wherever possible, the mathematics has been simplified. The guide is intended for use by graduates and researchers in bioinformatics and the life sciences and is also suitable for statisticians who are interested in the approaches currently used to study gene expression. Microarrays are an automated way of carrying out thousands of experiments at once, and allows scientists to obtain huge amounts of information very quickly Short, concise text on this difficult topic area Clear illustrations throughout Written by well-known teachers in the subject Provides insight into how to analyse the data produced from microarrays Trade Review"Quite a few recently published books discuss analysis of microarray gene expression data for beginners. Microarray Gene Expression Data Analysis ... is arguably the best of its kind in this regard." Terry Speed, The Walter & Eliza Hall Institute of Medical Research, Nature Cell Biology, December 2003 "Overall this is an excellent book, it is well referenced and, to my mind, covers the vast majority of issues an experimenter needs to consider when venturing into the world of microarray data analysis. The book fills a clear gap in the field, providing a rigorous overview of the often confusing .... data analysis issues that most books on microarrays avoid or treat in a cursory way. I would say it is essential reading for any laboratory or researcher active in this rapidly evolving field and is recommended for the mathematician or statisitican who is interested in the field or who has been persuaded by their biologist colleague to help them with their analysis." Steven Russell, University of Cambridge, Genetical Research, February 2003 "Anyone wishing to gain a basic understanding of microarray gene expression studies will come away enriched ... A good and accessible entry point for any biologist who is interested in getting an overview about how to perform microarray gene expression studies." D.C.Jamison, George Mason University, Heredity, June 2004Table of ContentsPreface. Acknowledgements. Part I: Introduction:. 1. What Are Microarrays?. 2. Use Of Icroarrays To Monitor Gene Expression. 3. Other Uses For Microarrays. 4. Challenges Associated With The Generation Of Large Amounts Of Complex Data. 5. Future Directions. Part II: Aspects Of Experimental Design:. 6. Features Of Microarray Data. 7. Designing The Best Experiment. 8. Preparation of Target. 9. Design of Spotted Arrays. 10. Hybridisation. 11. Long Term Considerations. 12. Verification of Results. Part III: Data Analysis:. 13. Preliminary Processing of Data. 14. Methods for Data Analysis. 15. Graph Models. 16. Software In The Public Domain. 17. Visualisation of Data. Part IV: Glossary:. Index. Colour plates fall between pp. 84 and 85.
£73.76
John Wiley and Sons Ltd Biomolecular Archaeology
Book SynopsisIllustrated thoroughly, Biomolecular Archaeology is the first book to clearly guide students through the study of ancient DNA: how to analyze biomolecular evidence (DNA, proteins, lipids and carbohydrates) to address important archaeological questions. The first book to address the scope and methods of this new cross-disciplinary area of research for archaeologists Offers a completely up-to-date overview of the latest research in this innovative subject Guides students who wish to become biomolecular archaeologists through the complexities of both the scientific methods and archaeological goals. Provides an essential component to undergraduate and graduate archaeological research Trade Review"Thenumerous figures and tables are clear and useful throughout, and a valuableglossary is also provided." (Journalof the Royal Anthropological Institute, 25 January 2013)Table of ContentsList of Figures. List of Tables. Preface. Part I: Biomolecules and How They Are Studied. Chapter 1 What is Biomolecular Archaeology? Chapter 2 DNA. Chapter 3 Proteins. Chapter 4 Lipids. Chapter 5 Carbohydrates. Chapter 6 Stable Isotopes. Part II: Preservation and Decay of Biomolecules in Archaeological Specimens. Chapter 7 Sources of Ancient Biomolecules. Chapter 8 Degradation of Ancient Biomolecules. Chapter 9 The Technical Challenges of Biomolecular Archaeology. Part III: The Applications of Biomolecular Archaeology. Chapter 10 Identifying the Sex of Human Remains. Chapter 11 Identifying the Kinship Relationships of Human Remains. Chapter 12 Studying the Diets of Past People. Chapter 13 Studying the Origins and Spread of Agriculture. Chapter 14 Studying Prehistoric Technology. Chapter 15 Studying Disease in the Past. Chapter 16 Studying the Origins and Migrations of Early Modern Humans. Glossary. Index.
£32.36
Taylor & Francis Inc Chromosome Nanoscience and Technology
Book SynopsisDespite progress in genetic research, knowledge about the exact structure of the chromosome continues to provide a challenge. Much of that challenge lies with the need for improved tools and methods that researchers require to perform novel analyses beyond the DNA level. Fortunately, rapid advances in nanotechnology, are now being employed to examine, analyze, and manipulate biological material at the chromosome level. Chromosome Nanoscience and Technology reviews these advances and their contribution to trends and applications in chromosome research. In addition to offering a guide to current progress, this book serves as the culminating report on a Japanese nanobiology project in the field of chromosome science begun in 2000. The project brought together researchers from disparate backgrounds that included molecular biology, biochemistry, protein science, immunology, genetics, anatomy, semiconductor production, polymer chemistry, material science, microscopy, and inforTable of ContentsPreface. Mechanical Approaches to Elucidate Mechanisms of Chromosome Condensation at the Nano- and Micro-Level. Development of Novel AFM Probes for Chromosome Manipulation. Microchamber Array-Based Sequence-Specific DNA Detection from a Single Chromosome via Trace Volume PCR. On-Chip Chromosome Sorter Using Electric and Magnetic Fields. Fluorescence Microscopy for Analysis of Chromosome Dynamics. Fluorescence In Situ Hybridization (FISH) as a Tool for Comparative Genomics. Immunocytochemistry for Analyzing Chromosomes. Transmission and Scanning Electron Microscopy of Mammalian Metaphase Chromosomes. Atomic Force Microscopy of Human Chromosomes in Relation to Their Higher-Order Structure. Mechanism of Higher-Order Chromatin Folding Revealed by AFM Observation of In Vitro Reconstituted Chromatin. Scanning Near-Field Optical/Atomic Force Microscopy as a Tool for Simultaneous Specification of Chromosome Topography and Particular Gene Location on the Nanometer Scale. Isolation of Human and Plant Chromosomes as Nano-Materials. Proteome Analysis of Human Metaphase Chromosomes. Anti-Peptide Antibodies for Examining the Conformation and Molecular Assembly of an Intracellular Protein. Structure and Interactions of the Imitation SWI-Type Chromatin-Remodeling Complex, ATP-Dependent Chromatin-Assembly Factor. Dynamic and Functional Analysis of Chromosomal Proteins. Development of a Sustainable Chromosome Imaging Database. Image Database and Image Analysis of Chromosome Information.
£171.00
