Computational biology / bioinformatics Books

Book SynopsisThis volume constitutes the proceedings of the 10th International Work-Conference on IWBBIO 2023, held in Meloneras, Gran Canaria, Spain, during July 12-14, 2022. The total of 79 papers presented in the proceedings, was carefully reviewed and selected from 209 submissions. The papers cove the latest ideas and realizations in the foundations, theory, models, and applications for interdisciplinary and multidisciplinary research encompassing disciplines of computer science, mathematics, statistics, biology, bioinformatics, and biomedicine.

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Book SynopsisThis volume constitutes the proceedings of the 10th International Work-Conference on IWBBIO 2023, held in Meloneras, Gran Canaria, Spain, during July 12-14, 2022. The total of 79 papers presented in the proceedings, was carefully reviewed and selected from 209 submissions. The papers cove the latest ideas and realizations in the foundations, theory, models, and applications for interdisciplinary and multidisciplinary research encompassing disciplines of computer science, mathematics, statistics, biology, bioinformatics, and biomedicine.

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Book SynopsisThis book constitutes the proceedings of the 16th Brazilian Symposium on Bioinformatics on Advances in Bioinformatics and Computational Biology, BSB 2023, which took place in Curitiba, Brazil, in June 2023. The 11 full papers and 3 short papers presented in this volume were carefully reviewed and selected from 24 submissions. The papers focus on bioinformatics, computational biology, Biological Databases, Biological Networks, Cheminformatics, Evolutionary Genomics, Computational Proteomics, Systems Biology, Drug Design, Genomics, Machine Learning applications in Bioinformatics, Metagenomics, Molecular Docking and Modeling, Molecular Evolution and Phylogenetics, Protein Structure and Modeling, Proteomics, Transcriptomics, Single-Cell Analysis, Workflows in Bioinformatics. Table of ContentsBlock Interchange and Reversal Distance on Unbalanced Genomes.- circTIS: a weighted degree string kernel with support vector machine tool for translation initiation sites prediction in circRNA.- Evaluating the molecular-electronic structure and the antiviral effect of functionalized heparin on graphene oxide through ab initio computer simulations and molecular docking.- Make No Mistake! Why Do Tools Make Incorrect Long Non-Coding Rna Classification?.- Spectrum-Based Statistical Methods for Directed Graphs with Applications in Biological Data.- Feature Selection Investigation in Machine Learning Docking Scoring Functions.- Using natural language processing for context identification in COVID-19 literature.- A framework for inference and selection of cell signaling pathway dynamic models.- Intentional Semantics for Molecular Biology.- transcAnalysis: A Snakemake Pipeline for Differential Expression and Post-Transcriptional Modification Analysis.- Peptide-protein interface classification using convolutional neural networks.- A Power Law Semantic Similarity from Gene Ontology.- Gene Networks Inference by Reinforcement Learning Approach.- Exploring Identifiability in Hybrid Models of Cell Signaling Pathways.

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Book SynopsisThis book constitutes the refereed conference proceedings of the 14th International Conference on Bio-inspired Information and Communications Technologies, held in Okinawa, Japan, during April 11-12, 2023. The 17 full papers were carefully reviewed and selected from 33 submissions. The papers focus on the latest research that leverages the understanding of key principles, processes, and mechanisms in biological systems for development of novel information and communications technologies (bio-inspired ICT). BICT 2023 will also highlight innovative research and technologies being developed for biomedicine that are inspired by ICT (ICT-inspired biomedicine).Table of ContentsElectromagnetic-induced Calcium signal with network coding for molecular communications.- Smart Farm Teaching Aids based on STEM concepts.- Reinforcement Learning for Multifocal Tumour Targeting.- Automatic Soil Testing Device for Agriculture.- A Novel Visualization Method of Vessel Network for tumour Targeting: A Vessel Matrix Approach.- Heterogeneous Group of Fish Response to Escape Reaction.- Modeling and Simulation of a Bio-inspired Nanorobotic Drug Delivery System.- Cooperative Relaying in Multi-Hop Mobile Molecular Communication via Diffusion.- Covid-19 Versus Monkeypox-2022: The Silent Struggle of Global Pandemics.- Monte Carlo Simulation of Arbitrium and the Probabilistic Behavior of Bacteriophages.- Instant Messaging Application for 5G Core Network.- Genetic Algorithm-based Fair Order Assignment Optimization of Food Delivery Platform.- Preliminary Considerations on Non-Invasive Home-Based Bone Fracture Healing Monitoring.- Features of Audio Frequency Content of Respiration to Distinguish Inhalation from Exhalation.- Management of the medical file in case of emergency.- A Novel Durable Fat Tissue Phantom for Microwave Based Medical Monitoring Applications.- ISI Mitigation with Molecular Degradation in Molecular Communication.- Signal Transmission Through Human Body Via Human Oxygen Saturation Detection.- Simple ISI-Avoiding and Rate-Increasing Modulation for Diffusion-base Molecular Communications.- Range Expansion in Neuro-spike Synaptic Communication: Error Performance Analysis.- [Extended Abstract] Collective Bio-nanomachine Rotation via Chemical and Physical Interactions: A Three- dimensional Model.- Wearable Vibration Device to Assist with Ambulation for the Visually Impaired.- Development of Capacitive Sensors to Detect and Quantify Fluids in the Adult Diaper.- Energy Cyber Attacks to Smart Healthcare Devices: A Testbed.- [Extended Abstract] Wet-laboratory Experiments and Computer Simulation of Interacting Cell Spheroids.- Ensembles of Heuristics and Computational Optimisation In Highly Flexible Manufacturing System.- A Intelligent Nanorobots Fish Swarm Strategy for Tumor Targetting.- [Extended abstract] Design and Implementation of A General-purpose Multicellular Molecular Communication Simulator.

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Book SynopsisThis two-volume work focuses on the mathematical aspects of Darwinian evolution starting from the basic model of stochastic evolution of a single isolated locus in the presence of mutation to the multi–locus models of sexual and asexual populations. Volume 2 discusses the inference of fi tness landscape from DNA sequence data, discovery of the evolutionary roles of enygmatic traits, co-evolution of adversarial species, and various applications to virus evolution.

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Book SynopsisThis book is an introduction to mathematical biology for students with no experience in biology, but who have some mathematical background. The work is focused on population dynamics and ecology, following a tradition that goes back to Lotka and Volterra, and includes a part devoted to the spread of infectious diseases, a field where mathematical modeling is extremely popular. These themes are used as the area where to understand different types of mathematical modeling and the possible meaning of qualitative agreement of modeling with data. The book also includes a collections of problems designed to approach more advanced questions. This material has been used in the courses at the University of Trento, directed at students in their fourth year of studies in Mathematics. It can also be used as a reference as it provides up-to-date developments in several areas.Trade Review“The book introduces the reader into several ways of mathematical modelling, and also gives explanations on the relation between the different aspects. The structure of the book is very logical and it is easy to read and understand. … A rich collection of problems … can be found at the end of each chapter, which help to introduce students into the process of modelling through own experience. … it also provides up-to-date results in several of the topics included.” (Attila Dénes, Acta Scientiarum Mathematicarum, Vol. 81 (3-4), 2015)“The book under review is based on an introductory course on the mathematical modeling of biological phenomena. This is a textbook for students of mathematical sciences to accompany an advanced undergraduate course in the modeling of population dynamics using ordinary differential, delay differential, stochastic and difference equations. … It is a good introduction for those beginners that are interested in the fast growing field of mathematical biology.” (Leonid Berezanski, zbMATH, Vol. 1305, 2015)Table of Contents1 Malthus, Verhulst and all that.- 2 Delayed population models.- 3 Models of discrete-time population growth.- 4 Stochastic modeling of population growth.- 5 Spatial spread of a population.- 6 Prey-predator models.- 7 Competition among species.- 8 Mathematical modeling of epidemics.- 9 Models with several species and trophic levels.- 10 Appendices: A Basic theory of Ordinary Differential Equations; B Delay Equations; C Discrete dynamics; D Continuous-time Markov chains.

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Book SynopsisThis book on mathematical modeling of biological processes includes a wide selection of biological topics that demonstrate the power of mathematics and computational codes in setting up biological processes with a rigorous and predictive framework. Topics include: enzyme dynamics, spread of disease, harvesting bacteria, competition among live species, neuronal oscillations, transport of neurofilaments in axon, cancer and cancer therapy, and granulomas. Complete with a description of the biological background and biological question that requires the use of mathematics, this book is developed for graduate students and advanced undergraduate students with only basic knowledge of ordinary differential equations and partial differential equations; background in biology is not required. Students will gain knowledge on how to program with MATLAB without previous programming experience and how to use codes in order to test biological hypothesis.Trade Review“This is a course book on several topics from mathematical biology. … The book provides a short introduction to ordinary differential equations, partial differential equations, bifurcation theory and numerical methods for dynamical systems. … The book is a valuable support for teaching mathematical modeling in life sciences to students with basic knowledge of ordinary differential equations and partial differential equations.” (Maria Vittoria Barbarossa, Acta Scientiarum Mathematicarum, Vol. 81 (3-4), 2015)“Each section begins with a biological background and ends by a numerical implement of an according mathematical model. The student can freely use these tools for simulations. With this book, the student also will learn the basics of mathematical modeling with Matlab. The book can be used either for a semester course or as a basis for a one-year course.” (Fatima T. Adylova, zbMATH, Vol. 1302, 2015)Table of ContentsIntroduction.- Chemical Kinetics and Enzyme Dynamics.- Ordinary Differential Equations.- Epidemiology of Infectious Diseases.- Chemostats and Competition Among Species.- Bifurcation Theory.- Neuronal Oscillations.- Conservation Laws.- Neurofilaments Transport in Axon.- Diffusion and Chemotaxis.- Cancer.- Cancer Therapy.- Granulomas.- Bibliography.- Answers to Problems.

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Book SynopsisThis book presents advanced expression technologies for the production of protein complexes. Since complexes lie at the heart of modern biology, the expression, purification, and characterization of large amounts of high-quality protein complexes is crucial for the fields of biomedicine, biotechnology, and structural biology. From co-expression in E. coli, yeast, mammalian and insect cells to complex reconstitution from individual subunits, this book offers useful insights and guidance for successful protein expressionists. Across several sections readers will discover existing opportunities for the production of protein complexes in bacterial systems (including membrane proteins and cell-free co-expression), methylotrophic and non-methylotrophic yeasts, protozoa (Leishmania terantolae and Dictyostelium discoideum), baculovirus-infected insect cells, mammalian cells, plants and algae. Complex reconstitution from individually purified subunits or subcomplexes is discussed as a complementary strategy. A last section introduces briefly some of the biophysical and structural characterization techniques for macromolecular complexes using state-of-the-art solution scattering and nuclear magnetic resonance. This work is a guided tour over some of the most powerful and successful protein expression technologies, with a focus on co-expression and high-throughput applications. It is addressed to everyone interested in the production and characterization of macromolecular complexes, from university students who want an accessible description of the major co-expression systems to researchers in biomedicine and the life sciences seeking for an up-to-date survey of available technologies.Table of ContentsPreface. Complex Biologics: Engineering the Tools and the Hosts. M. Cristina Vega, Francisco J. Fernández and Imre Berger Section 1: Introduction 1. Protein complex production from the drug discovery standpoint; Ismail Moarefi <2. Choose a suitable expression host: a survey of available protein production platforms; Francisco J. Fernández and M. Cristina Vega Section 2: Prokaryotic expression hosts 3. ACEMBL Tool-Kits for High-Throughput Multigene Delivery and Expression in Prokaryotic and Eukaryotic Hosts; Yan Nie, Maxime Chaillet, Christian Becke, Matthias Haffke, Martin Pelosse, Daniel Fitzgerald, Ian Collinson, Christiane Schaffitzel and Imre Berger 4. Complex reconstitution and characterization by combining co-expression techniques in Escherichia coli with high-throughput; Renaud Vincentelli and Christoph Romier 5. Membrane protein production in E. coli for applications in drug discovery; Harm Jan (Arjan) Snijder and Jonna Hakulinen6. Cell-free Synthesis of Macromolecular Complexes; Matthieu Botte, Aurélien Deniaud and Christiane Schaffitzel 7. A Bacillus megaterium system for the production of recombinant proteins and protein complexes; Rebekka Biedendieck 8. Protein complex production in alternative prokaryotic hosts; Sara Gómez, Miguel López-Estepa, Francisco J. Fernández and M. Cristina Vega Section 3: Lower Eukaryotic expression hosts 9. Production of Protein Complexes in Non-methylotrophic and Methylotrophic Yeasts; Francisco J. Fernandez, Miguel López-Estepa, Javier Querol-García and M. Cristina Vega 10. Leishmania tarentolae for the Production of Multi-Subunit Complexes; Tomoaki Niimi 11. Alternative Eukaryotic Expression Systems for the Production of Proteins and Protein Complexes; Sara Gómez, Miguel López-Estepa, Francisco J. Fernández, Teresa Suárez and M. Cristina Vega Section 4: Higher Eukaryotic expression hosts 12. Fundamentals of baculovirus expression and applications; Tom A. Kost and Christopher W. Kemp 13. The MultiBac Baculovirus / Insect Cell Expression Vector System for Producing Complex Protein Biologics; Duygu Sari, Kapil Gupta, Deepak Balaji Govinda Raj, Alice Aubert, Petra Dmcova, Frederic Garzoni, Daniel Fitzgerald and Imre Berger 14. Fundamentals of expression in mammalian cells; Michael R. Dyson 15. Assembling multi-subunit complexes using mammalian expression; Bahar Baser and Joop van den Heuvel Section 5: Plant expression 16. Microalgae as solar-powered protein factories; Franziska Hempel and Uwe G. Maier 17. Strategies and methodologies for the co-expression of multiple proteins in plants; Albert Ferrer, Montserrat Arró, David Manzano and Teresa Altabella 18. Transient expression systems in plants—potentialities and constraints; Tomas Canto Section 6: Complex reconstitution 19. Complex reconstitution from individual protein modules; Jérome Basquin, Michael Taschner and Esben Lorentzen 20. Structural reconstruction of protein-protein complexes involved in intracellular signaling; Klára Kirsch, Péter Sok, and Attila Remény Section 7: Biophysical methods to assess protein complexes 21. The use of small-angle scattering for the characterization of multi subunit complexes; Adam Round22. Application of nuclear magnetic resonance and hybrid methods to structure determination of complex systems. Filippo Prischi and Annalisa Pastore

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Book SynopsisThis book draws on Mark Mc Auley’s wealth of experience to provide an intuitive step-by-step guide to the modelling process. It also provides case studies detailing the creation of biological process models. Mark Mc Auley has over 15 years’ experience of applying computing to challenges in bioscience. Currently he is employed as a Senior Lecturer in Chemical Engineering at the University of Chester. He has published widely on the use of computer modelling in nutrition and uses computer modelling to both enhance and enrich the learning experience of the students that he teaches. He has taught computer modelling to individuals at a wide variety of levels and from different backgrounds, from undergraduate nutrition students to PhD and medical students.Table of Contents1. Introduction2. Building a computer model for nutrition research3. Model simulation and software4. Parameter optimisation and sensitivity analysis5. Modelling cholesterol metabolism and ageing6. Modelling Fatty acid metabolism7. Modelling Folate metabolism and DNA methylation8. Conclusions.

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Book SynopsisThe aim of these lecture notes is to give an introduction to several mathematical models and methods that can be used to describe the behaviour of living systems. This emerging field of application intrinsically requires the handling of phenomena occurring at different spatial scales and hence the use of multiscale methods.Modelling and simulating the mechanisms that cells use to move, self-organise and develop in tissues is not only fundamental to an understanding of embryonic development, but is also relevant in tissue engineering and in other environmental and industrial processes involving the growth and homeostasis of biological systems. Growth and organization processes are also important in many tissue degeneration and regeneration processes, such as tumour growth, tissue vascularization, heart and muscle functionality, and cardio-vascular diseases.Table of ContentsPreface.- Cell-based, continuum and hybrid models of tissue dynamics.- The Diffusion Limit of Transport Equations in Biology.- Mathematical Models of the Interaction of Cells and Cell Aggregates with the Extracellular Matrix.- Mathematical modeling of morphogenesis in living materials.- Multiscale computational modelling and analysis of cancer invasion.

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Book SynopsisThis textbook provides an exciting new addition to the area of network science featuring a stronger and more methodical link of models to their mathematical origin and explains how these relate to each other with special focus on epidemic spread on networks. The content of the book is at the interface of graph theory, stochastic processes and dynamical systems. The authors set out to make a significant contribution to closing the gap between model development and the supporting mathematics. This is done by: Summarising and presenting the state-of-the-art in modeling epidemics on networks with results and readily usable models signposted throughout the book; Presenting different mathematical approaches to formulate exact and solvable models; Identifying the concrete links between approximate models and their rigorous mathematical representation; Presenting a model hierarchy and clearly highlighting the links between model assumptions and model complexity; Providing a reference source for advanced undergraduate students, as well as doctoral students, postdoctoral researchers and academic experts who are engaged in modeling stochastic processes on networks; Providing software that can solve differential equation models or directly simulate epidemics on networks. Replete with numerous diagrams, examples, instructive exercises, and online access to simulation algorithms and readily usable code, this book will appeal to a wide spectrum of readers from different backgrounds and academic levels. Appropriate for students with or without a strong background in mathematics, this textbook can form the basis of an advanced undergraduate or graduate course in both mathematics and other departments alike. Trade Review“The book adds to the knowledge of epidemic modeling on networks by providing a number of rigorous mathematical arguments and confirming the validity and optimal range of applicability of the epidemic models. It serves as a good reference guide for researchers and a comprehensive textbook for graduate students.” (Yilun Shang, Mathematical Reviews, November, 2017)“This is one of the first books to appear on modeling epidemics on networks. … This is a comprehensive and well-written text aimed at students with a serious interest in mathematical epidemiology. It is most appropriate for strong advanced undergraduates or graduate students with some background in differential equations, dynamical systems, probability and stochastic processes.” (William J. Satzer, MAA Reviews, September, 2017)Table of ContentsPreface.- ​Introduction to Networks and Diseases.- Exact Propagation Models: Top Down.- Exact Propagation Models: Bottom-Up.- Mean-Field Approximations for Heterogeneous Networks.- Percolation-Based Approaches for Disease Modelling.- Hierarchies of SIR Models.- Dynamic and Adaptive Networks.- Non-Markovian Epidemics.- PDE Limits for Large Networks.- Disease Spread in Networks with Large-scale structure.- Appendix: Stochastic Simulation.- Index.

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Book SynopsisThis book develops the mathematical tools essential for students in the life sciences to describe interacting systems and predict their behavior. From predator-prey populations in an ecosystem, to hormone regulation within the body, the natural world abounds in dynamical systems that affect us profoundly. Complex feedback relations and counter-intuitive responses are common in nature; this book develops the quantitative skills needed to explore these interactions. Differential equations are the natural mathematical tool for quantifying change, and are the driving force throughout this book. The use of Euler’s method makes nonlinear examples tractable and accessible to a broad spectrum of early-stage undergraduates, thus providing a practical alternative to the procedural approach of a traditional Calculus curriculum. Tools are developed within numerous, relevant examples, with an emphasis on the construction, evaluation, and interpretation of mathematical models throughout. Encountering these concepts in context, students learn not only quantitative techniques, but how to bridge between biological and mathematical ways of thinking. Examples range broadly, exploring the dynamics of neurons and the immune system, through to population dynamics and the Google PageRank algorithm. Each scenario relies only on an interest in the natural world; no biological expertise is assumed of student or instructor. Building on a single prerequisite of Precalculus, the book suits a two-quarter sequence for first or second year undergraduates, and meets the mathematical requirements of medical school entry. The later material provides opportunities for more advanced students in both mathematics and life sciences to revisit theoretical knowledge in a rich, real-world framework. In all cases, the focus is clear: how does the math help us understand the science?Trade Review“The book can serve as an introduction to the field of modeling not only for university students but for any person interested in the field with little or no knowledge of calculus. … This book is a very interesting deviation from this prevailing paradigm. It takes the essence of calculus and presents it in a way which is accessible and usable in the practice of life sciences professionals.” (Svetoslav Markov, zbMATH 1397.92001, 2018)Table of Contents1. Modeling, Change, and Simulation.- 2. Derivatives and Integrals.- 3. Equilibrium Behavior.- 4. Non-Equilibrium Dynamics: Oscillation.- 5. Chaos.- 6. Linear Algebra.- 7. Multivariable Systems.- Bibliography.- Index.

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Book SynopsisWritten with biologists, biochemists and other molecular scientists in mind, this volume meets the long-felt need for a textbook dedicated to the topic and recreates the excitement surrounding the scientific revolution sparked by the discovery of RNA interference in 1998. Students and instructors alike will profit from the author's exclusive first-hand knowledge, drawing on his breakthrough discoveries at the Tuschl lab at Rockefeller University. Gunter Meister abandons the traditionalist treatment of nucleic acids found in most biochemistry and molecular biology texts, adopting instead a modern approach in both concept and scope. The text is divided into three parts, on mRNA, non-coding RNA, and RNomics, and the author addresses the traditional roles of RNA in the transmission and regulation of genetic information, as well as the recently discovered functions of small RNA species in pathogen defense, cell differentiation and higher-level genomic regulation. All set to become the standard for teaching molecular science to biologists and biochemists.Trade Review"In summary, Gunter Meister has compiled a most timely textbook that gives an excellent overview of the fundamental biological role of RNA molecules. The book is a valuable resource of information for anyone interested in RNA biology. Its content goes well beyond the scope of standard molecular biology or biochemistry textbooks." (ChemMedChem, 2011) "Meister (biochemistry, U. of Regensburg, Germany) covers RNA biology comprehensively without getting into mechanistic detail, to provide an introduction for undergraduate students of all life sciences. Chapter-end references point to fuller treatments for students who are interested." (Book News, 1 October 2011) Table of ContentsPreface xv Part One mRNA Biology 1 1 Introduction 3 1.1 RNA Building Blocks 4 1.2 RNA Folding 6 1.3 The RNA World Hypothesis 10 1.4 Functions of RNA 11 1.5 Protein Classes that are Required for RNA Function 12 1.5.1 RNA Binding Proteins 12 1.5.1.1 Proteins that Interact with Single Stranded RNAs 12 1.5.1.2 Proteins that Interact with Double Stranded RNAs 14 1.5.2 RNA Helicases 14 References 15 2 Transcription of Pre-mRNAs 17 2.1 Structure and Organization of Protein Coding Genes 18 2.2 Transcription of Mrnas by Rna Polymerase II 20 2.2.1 Transcriptional Initiation of Protein Coding Genes 23 2.2.2 Regulation of Transcriptional Initiation of Rna Polymerase II 27 2.2.3 Transition from Preinitiation to Initiation and Promoter Clearance 27 2.2.4 Productive Elongation of mRNA Transcripts 29 2.2.4.1 The Nucleotide Addition Cycle (NAC) 29 2.2.4.2 Protein Factors that Influence Pol II Elongation 30 2.3 Transcriptional Termination of Pre-mRNAs 31 2.4 Transcription is Coupled to Other mRNA Maturation Steps 32 2.5 Summary 34 References 35 3 Capping of the Pre-mRNA 5 0 End 37 3.1 m 7 G-cap Structure 37 3.2 mRNA Capping Enzymes 39 3.2.1 RNA Triphosphatase 39 3.2.2 Guanylyltransferase 39 3.2.3 Guanine-N7-Methyltransferase 40 3.3 5 0 Capping is Coupled to Transcription 41 3.4 5 0 Cap Binding Proteins 41 3.5 Summary 42 References 43 4 3 0 End Processing of Pre-mRNAs 45 4.1 Polyadenylation Signals 46 4.2 Proteins Involved in 3 0 End Processing of Pre-mRNAs 47 4.2.1 Cleavage and Polyadenylation Specific Factor (CPSF) 47 4.2.2 Cleavage Stimulation Factor (CstF) 47 4.2.3 Mammalian Cleavage Factor I (CFI m) and II (CFII m) 48 4.2.4 The Poly(A) Polymerase (PAP) 49 4.2.5 Poly(A)-Binding Protein (PABP) 50 4.2.6 Symplekin 51 4.3 3 0 End Processing is Tightly Linked to Transcriptional Termination 51 4.4 Alternative Polyadenylation 51 4.5 Cytoplasmic Polyadenylation 53 4.6 3 0 End Processing of Histone mRNAs 54 4.7 Summary 56 References 57 5 Splicing of Eukaryotic Pre-mRNAs 59 5.1 Group I, II and III Introns 59 5.1.1 Group I Introns 59 5.1.2 Group II Introns 61 5.1.3 Group III Introns 61 5.2 The Mechanism of pre-mRNA Splicing 61 5.3 The Spliceosome 62 5.4 The U12-Dependent Minor Spliceosome 66 5.5 Coupling of Splicing with Transcription and 5 0 Capping 67 5.6 Alternative Splicing and the Complexity of Genomes 68 5.6.1 Mechanisms of Exon Inclusion into the Mature mRNA 69 5.6.2 Mechanism of Exon Exclusion from the Mature mRNA 70 5.7 Summary 70 5.8 Questions 71 References 72 6 mRNA Export from the Nucleus to the Cytoplasm 73 6.1 Nuclear Import and Nuclear Export 73 6.2 mRNA Export Receptors 75 6.3 Adaptors that Bridge mRNAs with Export Receptors 78 6.4 Mechanism of mRNA Export 78 6.5 Coupling of mRNP Export to Other Steps of mRNA Maturation 80 6.6 Summary 80 6.7 Questions 81 References 81 7 Translation 83 7.1 Amino Acids, mRNAs, tRNAs 83 7.1.1 mRNA 83 7.1.2 Amino Acids 84 7.1.3 Transfer RNAs (tRNAs) 86 7.1.4 Loading Amino Acids onto tRNAs 87 7.2 The Ribosome 89 7.3 The Mechanisms of Translation 90 7.3.1 Translation Initiation 90 7.3.1.1 Eukaryotes 90 7.3.1.2 Bacteria 93 7.3.1.3 Archaea 96 7.3.1.4 Internal Ribosome Entry Sites (IRESs) 96 7.3.2 Elongation 97 7.3.2.1 Polyribosomes 97 7.3.3 Termination 99 7.3.4 Recycling of the Ribosome 100 7.4 Translational Regulation 100 7.4.1 Regulation of Translation Initiation 100 7.4.2 Regulation of Translation Elongation and Termination 103 7.5 Coupling Translation with Other mRNA Maturation and Quality Control Steps 103 7.6 Summary 104 7.7 Questions 105 References 106 8 Deadenylation of mRNA 107 8.1 Deadenylating Enzymes 107 8.1.1 Poly(A) Nuclease 107 8.1.2 CCR4-NOT Complex 108 8.1.3 Poly(A) Ribonuclease 108 8.1.4 Other Deadenylases 110 8.2 Summary 111 8.3 Questions 111 References 112 9 mRNA Decapping 113 9.1 Decapping Enzymes are the Core of the mRNA Decapping Machinery 113 9.2 Scavenger Decapping Enzyme DcpS 115 9.3 Regulation of mRNA Decapping 115 9.3.1 Inhibitors of Decapping 115 9.3.2 Enhancers of Decapping 116 9.4 Intracellular Localization of mRNA Decapping 117 9.5 Summary 118 9.6 Questions 119 References 119 10 mRNA Decay Pathways 121 10.1 Deadenylation-Dependent mRNA Decay 122 10.1.1 The 5 0 to 3 0 Exoribonuclease Xrn 1 122 10.1.2 The Exosome 122 10.1.2.1 Structural Organization of the Exosome 125 10.1.2.2 Mechanism of Exosome-Mediated RNA Degradation 125 10.1.2.3 Regulation of Exosome Activity 126 10.2 Deadenylation-Independent mRNA Decay 127 10.3 Endoribonuclease-Mediated mRNA Decay 128 10.3.1 Eukaryotic Endoribonucleases 129 10.4 Regulation of mRNA Decay 131 10.5 RNA Degradation in Bacteria 131 10.6 Summary 133 10.7 Questions 134 References 135 11 mRNA Quality Control 137 11.1 Nuclear mRNA Quality Control Mechanisms 137 11.1.1 MRNP Retention at the Transcription Site 138 11.1.2 MRNP Quality Control at the Nuclear Pore Complex 138 11.2 Nonsense-Mediated mRNA Decay (NMD) 138 11.2.1 Protein Factors Required for NMD 139 11.2.1.1 UPF Proteins 139 11.2.1.2 The Exon–Exon–Junction Complex (EJC) and Nmd 140 11.2.1.3 SMG Proteins and the Phosphorylation of UPF 1 141 11.2.2 Mechanism of NMD in Mammals 142 11.2.3 Cytoplasmic Processing Bodies and NMD 143 11.2.4 Mechanism of NMD in Yeast and Flies 144 11.2.5 mRNA Degradation Pathways in NMD 146 11.3 Other mRNA Quality Control Pathways 146 11.3.1 Non-Stop mRNA Degradation 146 11.3.2 No-Go mRNA Decay (NGD) 148 11.4 Summary 148 11.5 Questions 149 References 149 Part Two Non-Coding RNA Biology 151 12 Ribosomal RNAs and the Biogenesis of Ribosomes 153 12.1 Genomic Organization of Ribosomal RNA Genes 153 12.1.1 Bacteria and Archaea 153 12.1.2 Eukaryotes 155 12.1.2.1 28S, 18S and 5.8S rRNAs 155 12.1.2.2 5S rRNA 156 12.2 Transcription of Ribosomal RNA Genes 157 12.2.1 RNA Polymerase I 157 12.2.1.1 Initiation of Pol I Transcription 158 12.2.1.2 Promoter Clearance, Transcript Elongation and Termination of Pol I Transcription 160 12.2.1.3 Regulation of RNA Polymerase I Transcription 161 12.2.2 RNA Polymerase III and the Transcription of the 5S rRNA 162 12.2.2.1 Pol III Promoters 163 12.2.2.2 Transcription Initiation and Elongation of Rna Polymerase III 165 12.2.2.3 Initiation of Type 3 Promoters 167 12.2.2.4 Termination and Re-Initiation 168 12.3 Maturation of rRNAs 169 12.3.1 Small Nucleolar RNAs are Required for Pre-rRNA Processing 170 12.4 Assembly of Ribosomal Subunits 172 12.5 Nuclear Export of Ribosomal Subunits 174 12.6 Modification, Structure and Function of rRNAs 175 12.7 Summary 178 12.8 Questions 179 References 180 13 Transfer RNAs 183 13.1 Genomic Organization and Transcription of tRNA Genes 183 13.2 Processing to Mature tRNAs 184 13.2.1 5 0 Maturation of tRNAs by the RNase P Enzyme Complex 184 13.2.2 3 0 End Maturation of tRNAs 186 13.2.3 tRNA Splicing 188 13.3 tRNA Modifications 191 13.4 Nuclear Export of tRNAs 193 13.5 Tertiary Structure of tRNAs 194 13.6 Summary 196 References 197 14 The 7SL RNA and the Signal Recognition Particle 199 14.1 Architecture of the SRP 199 14.1.1 The SRP RNA 199 14.1.2 Protein Components of the SRP 201 14.1.2.1 Eukaryotes 201 14.1.2.2 Archaea and Bacteria 203 14.2 SRP-Mediated Protein Translocation 204 14.3 Summary 206 References 208 15 Regulation of Transcription: the 7SK Small Nuclear RNA 209 15.1 Architecture of the 7SK snRNA 209 15.1.1 The 7SK snRNA 209 15.1.2 Protein Components of the 7SK snRNP 210 15.2 The 7SK snRNP Functions as Transcriptional Regulator 212 15.2.1 P-TEFb Function in Transcription 212 15.2.2 Repression of P-TEFb by the 7SK snRNP 214 15.3 Other Small Non-Coding RNAs that Interfere with Transcription 214 15.3.1 The 6S RNA in Bacteria 214 15.3.2 Alu, B1 and B2 Non-Coding RNAs in Mammals 215 15.4 Summary 215 References 216 16 Small Nucleolar RNAs 217 16.1 Genomic Organization and snoRNA Transcription 217 16.2 Box H/ACA snoRNAs 218 16.3 Box C/D snoRNAs 221 16.4 Maturation of Functional snoRNPs 223 16.5 Orphan snoRNAs 224 16.6 The Telomerase RNP 226 16.7 Summary 227 References 228 17 Spliceosomal Small Nuclear RNAs 229 17.1 Transcription and Maturation of Spliceosomal snRNAs 229 17.1.1 Transcription of Spliceosomal snRNAs 229 17.1.2 snRNA Maturation 230 17.1.3 SnRNA Export to the Cytoplasm 231 17.2 The Structure of UsnRNPs 232 17.2.1 Secondary Structure of Spliceosomal snRNAs 232 17.2.2 Protein Composition of UsnRNPs 233 17.2.2.1 The Sm/LSm Core Structure 233 17.2.2.2 UsnRNP-Specific Proteins 235 17.3 Assembly of Spliceosomal snRNPs 237 17.3.1 Cytoplasmic Assembly of the Sm Core Domain 237 17.3.2 Formation of the Tri-Methyl Guanine Cap 240 17.3.3 Import of Assembled UsnRNPs into the Nucleus 241 17.4 Summary 242 17.5 Questions 243 References 244 18 Small Non-Coding RNAs and the Mechanism of Gene Silencing 245 18.1 Short Interfering RNAs and the Mechanism of RNA Interference 245 18.2 Dicer 248 18.3 RNA-Dependent RNA Polymerases 248 18.4 Argonaute Proteins 251 18.5 microRNAs and the Regulation of Gene Expression 251 18.5.1 MiRNA Biogenesis 251 18.5.2 Non-Canonical miRNA Biogenesis Pathways 253 18.5.3 miRNA Functions 255 18.5.3.1 miRNAs Can Act as siRNAs 255 18.5.3.2 miRNAs Inhibit Translation 255 18.5.3.3 miRNAs Induce Deadenylation and mRNA Decay 256 18.6 PiRNAs and the Regulation of Mobile Genetic Elements in the Germ Line 257 18.6.1 Transposons as Driving Force Behind Evolution 258 18.6.2 PiRNAs Control Transposon Expression 259 18.7 Small RNAs with Functions in Chromatin Regulation 261 18.8 The CRISPR System – A Bacterial and Archaeal Defense Mechanism 263 18.8.1 The CRISPR Locus 263 18.8.2 Acquisition of CRISPR-Mediated Resistance 264 18.8.3 Mechanism of CRISPR Activity 265 18.9 Summary 266 References 269 19 Long Non-Coding RNAs 271 19.1 The XIST Non-Coding RNA and X Chromosome Inactivation 271 19.1.1 The X-Chromosome Inactivation Center (XIC) 272 19.1.2 the Xist Non-coding Rna and the Mechanism of X Inactivation 272 19.1.3 Regulation of XIST Function 274 19.2 Dosage Compensation in Flies 275 19.3 Non-Coding RNAs and the Regulation of Imprinting 276 19.4 The Regulation of HOX Genes by Long Non-Coding RNAs 278 19.5 Long non-Coding RNAs are Common in Complex Genomes 278 19.6 Summary 278 References 280 20 RNA Editing 281 20.1 RNA Editing by U Insertions or Deletions 281 20.1.1 Mechanisms of U Insertions or Deletions 282 20.2 RNA Editing by Base Modification 283 20.2.1 c to U conversion 284 20.2.2 Adenine to Inosine Editing 286 20.2.2.1 Adenosine Deaminase Acting on RNA 287 20.2.2.2 Editing Site Selectivity 288 20.2.2.3 Biological Consequences of A to I Conversions 288 20.3 Summary 290 References 291 21 Ribozymes – Catalytic RNA Molecules 293 21.1 Identification of Catalytic RNAs 293 21.2 Mechanisms and Secondary Structures of Different Ribozymes 294 21.2.1 Group I Introns 294 21.2.2 RNase P 295 21.2.3 The Diels–Alderase Ribozyme 296 21.2.4 Hammerhead Ribozymes 298 21.2.5 The glmS Ribozyme 298 21.3 Summary 300 References 301 22 Riboswitches and RNA Sensors 303 22.1 Mechanisms of Riboswitch Function 303 22.2 Riboswitch Structures 305 22.3 RNA Thermometers 305 22.4 Summary 307 References 308 23 RNomics 309 23.1 ‘‘Omics’’ Approaches 309 23.2 Experimental RNA Profiling Strategies 310 23.2.1 Northern Blotting 310 23.2.2 Microarray 311 23.2.3 Quantitative PCR 313 23.2.4 RNA Fluorescent In Situ Hybridization 314 23.2.5 Next Generation Sequencing 314 23.3 RNA Biology and the Complexity of Genomes 315 23.4 Summary 315 References 318 Appendix: Answers to Questions 319 Index 355

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Book SynopsisThe mathematical models in this book are concerned with a variety of approaches to the manner in which the clinical radiologic treatment of human neoplasms can be improved. These improvements comprise ways of delivering radiation to the malignan­ cies so as to create considerable damage to tumor cells while sparing neighboring normal tissues. There is no unique way of dealing with these improvements. Accord­ ingly, in this book a number of different presentations are given. Each presentation has as its goal some aspect of the improvement, or optimization, of radiotherapy. This book is a collection of current ideas concerned with the optimization of human cancer radiotherapy. It is hoped that readers will build on this collection and develop superior approaches for the understanding of the ways to improve therapy. The author owes a special debt of thanks to Kathy Prindle who breezed through the typing of this book with considerable dexterity. TABLE OF CONTENTS Chapter GENERAL INTRODUCTION 1. 1 Introduction 1 1. 2 History of Cancer and its Treatment by Radiotherapy 8 1. 3 Some Mathematical Models of Tumor Growth 12 1. 4 Spatial Distribution of the Radiation Dose 20 Chapter 2 SURVIVAL CURVES FROM STATISTICAL MODELS 24 2. 1 Introduction 24 2. 2 The Target Model 26 2. 3 Single-hit-to-kill Model 27 2. 4 Multitarget, Single-hit Survival 29 2. 5 Multitarget, Multihit Survival 31 2. 6 Single-target, Multihit Survival 31 2.Table of Contents1 General Introduction.- 1.1 Introduction.- 1.2 History of Cancer and its Treatment by Radiotherapy.- 1.3 Some Mathematical Models of Tumor Growth.- 1.4 Spatial Distribution of the Radiation Dose.- 2 Survival Curves from Statistical Models.- 2.1 Introduction.- 2.2 The Target Model.- 2.3 Single-hit-to-kill Model.- 2.4 Multitarget, Single-hit Survival.- 2.5 Multitarget, Multihit Survival.- 2.6 Single-target, Multihit Survival.- 2.7 Properties of In Vitro Survival Curves.- 3 A Molecular Model of cell Survival.- 3.1 Introduction.- 3.2 The Molecular Model.- 3.3 Interpretations of the Molecular Model.- 4 Kinetic Models of Biological Radiation Response.- 4.1 Introduction.- 4.2 Basic Postulates in the Dienes Model.- 4.3 Low LET Kinetic Models with no Recovery.- 4.4 Further Discussion of the Models.- 4.5 Low LET Kinetic Models with Recovery.- 4.6 Low LET and High LET Kinetic Model with No Recovery.- 4.7 Other Kinetic Schemes: Sparsely-ionizing Radiation.- 4.8 Kinetic Schemes with Age-specific Compartments in the Cell Cycle.- 4.9 Thermal Potentiation of Cell Killing.- 5 Cell Survival after Successive Radiation Fractions.- 5.1 Introduction.- 5.2 Some Results in Connection with Instantaneous Cell Kill and Exponential Tumor Growth.- 5.3 Instantaneous Cell Kill Followed by Logistic Growth of Normal Tissue.- 5.4 Cohen’s Cell Population Kinetics Programs.- 5.5 A Model of Radiation Therapy with Resistant and Sensitive Cell Populations.- 5.6 Dose Fractionation and General Survival Curves.- 6 Optimization Models in Solid Tumor Radiotherapy.- 6.1 Introduction.- 6.2 Optimal Radiotherapy of Tumor Cells Based on Cumulative Radiation Effect and a Multitarget, Single-hit Survival Function.- 6.3 Optimal Radiotherapy of Tumor Cells Based on Cumulative Radiation Effect and an Exponential-quadratic Survival Expression.- 6.4 Fractionation Scheme with a Four Level Population Tumor Model.- 6.5 A Dynamic Programming Solution to the Problem of the Determination of Optimal Treatment Schedules.- 6.6 Optimal Treatment Schedules in Fractionated Radiation Therapy for Fischer’s Tumor Model.- 6.7 Optimal Radiation Schedules with Cell Cycle Analysis.- 7 Numerical Solution of Multistage Optimal Control Problems.- 7.1 Introduction.- 7.2 Continuous Time Optimal Control.- 7.3 Optimization of Multistage Systems.- 7.4 Multi-dimensional Optimization by Gradient Methods.- 7.5 Gradient Method with Penalty Function.- 7.6 A Numerical Scheme for a Nonlinear Problem.- 7.7 The Method of Conjugate Gradients.- 7.8 Discrete Dynamic Programming.- 8 Some Optimization Criteria in Radiotherapy.- 8.1 Introduction.- 8.2 Therapeutic Policy, Strategy and Tactics.- 8.3 Optimization and Clinical Trials.- 8.4 Score Functions and Age Response Functions.- 8.5 Comparison of Models Used in Optimization Procedures.- 8.6 The Complication Probability Factor.- 9 The Optimization of External Beam Radiation Therapy.- 9.1 Introduction.- 9.2 Some Approaches for Treatment Plans.- 9.3 Linear Programming.- 9.4 Linear Programming and Radiation Treatment Planning.- 9.5 Optimization of External Beam Radiation Therapy Using Nonlinear Programming.- 9.6 Quantitative Study of Relative Radiation Effects and Isoeffect Patterns.- 10 Reconstructive Tomography.- 10.1 Introduction.- 10.2 Reconstruction Algorithm.- 10.3 Numerical Approximations for the Attenuation Coefficient.- 10.4 Cross-sectional Absorption Density Reconstruction for Treatment Planning.- 10.5 Towards the Optimization of Dose Reduction in Computerized Tomography.- 10.6 Other Imaging Technologies.- Appendix 1.- Appendix 2.- Appendix 3.

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Book SynopsisTable of Contents1. Einleitung und Fragestellung.- 2. Allgemeines.- 2.1 Typische Beispiele aus der Literatur.- 2.1.1 University Group Diabetes Program (UGDP)-Studie.- 2.1.2 Coronary Drug Project (CDP) — Studie.- 2.1.3 Clofibrat Studie.- 2.2 Generelle Probleme.- 2.2.1 Inhalt von Zwischenauswertungen.- 2.2.2 Gründe für einen vorzeitigen Studienabbruch.- 2.2.3 Allgemeine methodische statistische Aspekte bei Zwischenauswertungen und Studienabbruch.- 3. Verfahrensübersicht.- 3.1 Offene Sequentialpläne.- 3.2 Geschlossene Sequentialpläne.- 3.3 Gruppensequentielle Pläne.- 3.4 Testverfahren für Lebensdauerdaten.- 3.5 Multivariate Methoden und multiple Vergleiche.- 3.6 Sonstige Verfahren.- 4. Gemischte Strategien.- 4.1 Formale Ableitung.- 4.2 Praktische Berechnung.- 4.3 Ergebnisse.- 4.4 Vergleiche mit den bisherigen Verfahren.- 5. Verfahrensvergleiche bei Lebensdauerdaten durch Simulation.- 5.1 Simulationsmodell.- 5.2 Simulation und Ergebnisse.- 6. Schlußfolgerungen.- 7. Zusammenfassung.- 8. Literatur.- 9. Anhang.

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Book SynopsisThe free-radical chemistry of DNA had been discussed in some detail in 1987 in my book The Chemical Basis of Radiation Biology. Obviously, the more recent developments and the concomitant higher level of understanding of mechanistic details are missing. Moreover, in the living cell, free-radical DNA damage is not only induced by ionizing radiation, but free-radical-induced DNA damage is a much more general phenomenon. It was, therefore, felt that it is now timely to review our present knowledge of free-radical-induced DNA damage induced by all conceivable free-radical-generating sources. Originally, it had been thought to include also a very important aspect, the repair of DNA damage by the cell’s various repair enzymes. Kevin Prise (Cancer Campaign, Gray Laboratory, L- don) was so kind to agree to write this part. However, an adequate description of this strongly expanding area would have exceeded the allocated space by much, and this section had to be omitted. The directors of the Max-Planck-Institut für Strahlenchemie (now MPI für Bioanorganische Chemie), Karl Wieghardt and Wolfgang Lubitz, kindly allowed me to continue to use its facilities after my retirement in 2001. Notably, our - brarian, Mrs. Jutta Theurich, and her right-hand help, Mrs. Rosemarie Schr- er, were most helpful in getting hold of the literature. I thank them very much. Without their constant help, this would have been very difficult indeed.Table of ContentsFormation of Reactive Free Radicals in an Aqueous Environment.- The Hydroxyl Radical.- Hydrogen Atom and Hydrated Electron.- Inorganic Radicals.- Carbon-Centered Radicals.- Heteroatom-Centered Radicals.- Peroxyl Radicals.- Polymer Radicals.- Nucleobases, Nucleosides and Nucleotides.- Polynucleotides and Single-Stranded DNA Fragments.- DNA and Double-Stranded Oligonucleotides.- Methods.

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Book SynopsisDer Autor steigt über biologische Fragestellungen in die Mathematik ein und stellt kurz, knapp und dennoch umfassend die mathematischen Grundlagen dar, die für Biologen relevant sind. Zu Beginn jedes Kapitels wird anhand einfacher Beispiele erläutert, wie ein mathematisches Modell überhaupt entsteht. Der Stoff ist so aufbereitet, dass die Schulmathematik als Voraussetzung ausreicht. Das neu angeeignete Wissen kann anhand von Übungsaufgaben (mit Lösungen) erprobt werden.Trade ReviewAus den Rezensionen: "In dem vom Springer-Verlag veröffentlichten Buch ‘Mathematik in der Biologie‘ gibt Erich Bohl einen detaillierten Einblick in die Bereiche der Mathematik, die für Biologen erforderlich und interessant sind. … Insgesamt verfügt das Buch über eine fachlich detaillierte Abhandlung wichtiger Themengebiete, die vor allem durch die Verwendung ausschließlich praktischer Beispiele sehr anschaulich und somit verständlich erklärt werden. Ebenfalls positiv sind zahlreiche Aufgaben inklusive Lösungen für das jeweilige Kapitel, die auch zur Übung beitragen …" (in: Ersti-Heft Fachschaft Uni Potsdam, Wintersemester 07/08, S. 31) "… Wie im Buchtitel geht es um Mathematik in der Biologie und nicht außerhalb. Bohls Mathematik geht von Beobachtungen der belebten Natur aus und möchte den Bioforschern helfen, ihre Experimente auszuwerten. Das Buch ist … ein Lehrbuch im klassischen Sinne. Mit ihm, einem Taschenrechner, einem Stift und einem Blatt Papier bekommt man eine gute Einführung in die für Biologen wichtigen mathematischen Grundlagen." (Ralph Schill, in: Laborjournal, 2008, Issue 9, S. 84 f.)Table of ContentsWarum verwendet ein Biologe eigentlich Mathematik?.- Grundbestandteile mathematischer Modellierung.- Evolutionen: Skalare Differentialgleichungen erster Ordnung.- Beschreibung von Vorgängen mit mehr als einer unabhängigen Variablen.- Rekonstruktion von Funktionen aus Zahlenpaaren: Lineare Datenanpassung.- Interaktionen zweier Populationen.- Lösungen der Übungsaufgaben.

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Book SynopsisThe Springer Handbook of Bio-/Neuro-Informatics is the first published book in one volume that explains together the basics and the state-of-the-art of two major science disciplines in their interaction and mutual relationship, namely: information sciences, bioinformatics and neuroinformatics. Bioinformatics is the area of science which is concerned with the information processes in biology and the development and applications of methods, tools and systems for storing and processing of biological information thus facilitating new knowledge discovery. Neuroinformatics is the area of science which is concerned with the information processes in biology and the development and applications of methods, tools and systems for storing and processing of biological information thus facilitating new knowledge discovery. The text contains 62 chapters organized in 12 parts, 6 of them covering topics from information science and bioinformatics, and 6 cover topics from information science and neuroinformatics. Each chapter consists of three main sections: introduction to the subject area, presentation of methods and advanced and future developments. The Springer Handbook of Bio-/Neuroinformatics can be used as both a textbook and as a reference for postgraduate study and advanced research in these areas. The target audience includes students, scientists, and practitioners from the areas of information, biological and neurosciences.With Forewords by Shun-ichi Amari of the Brain Science Institute, RIKEN, Saitama and Karlheinz Meier of the University of Heidelberg, Kirchhoff-Institute of Physics and Co-Director of the Human Brain Project.Trade ReviewFrom the book reviews:“This handbook is structured in 12 parts, covering a wide variety of notions associated with bio- and neuroinformatics … . The handbook is a valuable and timely resource, which can be used by undergraduates, postgraduates and established researchers. By presenting together a variety of (linked) approaches, it provides a fantastic source for bioinformaticians and neuroinformaticians alike.” (Irina Ioana Mohorianu, zbMATH, Vol. 1304, 2015)“This is the very best of the encyclopedias and comprehensive book’s about both Medical, Molecular, Genetic, and Neural Informatics currently available. … this is a good textbook for graduate students as a Primer on Neurophysiology and Molecular Medicine. Professionals in these areas will find this book very useful in their daily work … . book is very well referenced at the end of each chapter discussion. … I am pleased to recommend this book to new researchers in the field.” (Joseph J. Grenier, Amazon.com, November, 2014)Table of ContentsChap. 1 Understanding Nature - Symbiosis of Information Science, Bioinformatics and NeuroinformaticsPart A Understanding Information Processes in Biological Systems (Ed. Heike Sichtig)Chap. 2 Information Processing at the Cellular Level.- Chap. 3 Integrated Approaches for Understadning the Cell.- Chap. 4 Information Processing at the Genomics Level.- Chap. 5 Understanding Information Processes at the Proteomics Level.- Chap. 6 Pattern Formation and Animal Morphogenesis.- Chap. 7 Understanding Evolving Bacteria ColoniesPart B Molecular Biology, Genome and Proteome Informatics (Ed.: Chris Brown)Chap. 8 Exploring Interactions and Structural Organization of Genomes.- Chap. 9 Detecting microRNA Signatures Using Gene Expression Analysis.- Chap. 10 Bioinformatics Methods to Discover Cis-Regulatory Elements.- Chap. 11 Protein Modeling and Structural PredictionPart C Machine-Learning Methods (Eds: Irwin King, Kaizhu Huang, Heike Sichtig)Chap. 12 Machine Learning Methodology in Bioinformatics.- Chap. 13 Case-Based Reasoning for Biomedical Informatics and Medicine.- Chap. 14 Analysis of Multiple DNA Microarray Datasets.- Chap. 15 Fuzzy Logic and Rule-Based Methods in Bioinformatics.- Chap. 16 Phylogenetic Cladograms: Understanding and Learning from Biomedical Data.- Chap. 17 Understanding Protein Folding Modeling.- Chap. 18 Kernel Methods and Applications in BioinformaticsPart D Modeling Regulatory Networks: The Systems Biology Approach (Eds: Chris Brown, Heike Sichtig, Irwin King, Kaizhu Huang, Francesco Masulli)Chap. 19 Path Finding in Biological Networks.- Chap. 20 Inferring Transcription Networks from Data.- Chap. 21 Analysis of Transcriptional Regulation.- Chap. 22 Inferring Genetic Networks.- Chap. 23 Structural Pattern Discovery.- Chap. 24 Molecular Networks - Representation and Analysis.- Chap. 25 Whole-Exome Sequencing DataPart E Bioinformatics Databases and Ontologies (Ed.: Francesco Masulli)Chap. 26 Bioinformatics Databases.- Chap. 27 Ontologies for BioinformaticsPart F Bioinformatics in Medicine, Health and Ecology (Eds: Francesco Masulli, Danilo Mandic)Chap. 28 Statistical Signal Processing Models And Methods.- Chap. 29 Epigenetics.- Chap. 30 Control of Autoimmune Diseases.- Chap. 311 Nutrigenomics.- Chap. 32 Bioinformatics and Nanotechnologies: Nanomedicine.- Chap. 33 Information Modeling Technologies for Personalized Medicine.- Chap. 34 Health Informatics.- Chap. 35 Ecological Informatics Part G Understanding Information Processes in the Brain and the Nervous System (Ed.: Heike Sichtig)Chap. 36 Information Processing in Synapses.- Chap. 37 Spiking Neural Networks.- Chap. 38 Statistical Methods for fMRI Activation Detection.- Chap. 39 Neural Circuit Models and Neuropathological Oscillations.- Chap. 40 Understanding the Brain via fMRI ClassificationPart H Advanced Signal-Processing Methods for Brain Signal Analysis and Modeling (Ed.: Danilo Mandic)Chap. 41 Nonlinear Adaptive Filtering in Kernel Spaces.- Chap. 42 Analysis of Multiple Spike Trains.- Chap. 43 Adaptive Multiscale Time-Frequency AnalysisPart I Information Modeling of Perception, Sensation and Cognition (Eds: Lubica Benuskova, Heike Sichtig)Chap. 44 Modeling Vision with the Neocognitron.- Chap. 45 Information Processing in the Gustatory System.- Chap. 46 EEG Signal Processing for Brain Computer Interfaces.- Chap. 47 Spiking Neural Networks.- Chap. 48 Neurocomputational Models of Natural LanguagePart J Neuroinformatics Databases and Ontologies (Eds: Shiro Usui, Raphael Ritz)Chap. 49 Ontologies and Machine Learning Systems .- Chap. 50 Integration of Large-Scale NeuroinformaticsPart K Information Modeling for Brain Diseases (Eds: Lubica Benuskova, Francesco Masulli)Chap. 51 Alzheimer’s Disease.- Chap. 52 Integrating Data for Modeling Biological Complexity.- Chap. 53 A Machine Learning Pipeline .- Chap. 54 Modeling Gene-Dependent Dynamics of Cortex and Epilepsy.- Chap. 55 Information Methods for Predicting Stroke.- Chap. 56 Recognition of Rehabilitation ActionsPart L Nature Inspired Integrated Information Technologies(Eds: Lubica Benuskova, Danilo Mandic)Chap. 57 Brain-Like Robotics.- Chap. 58 Developmental Learning for User Activities.- Chap. 59 Quantum and Biocomputing - Common Notions and Targets.- Chap. 60 Brain-, Gene-, and Quantum-Inspired Computational Intelligence.- Chap. 61 The Brain and Creativity.- Chap. 62 The Allen Brain AtlasAcknowledgements.- About the Authors.- Subject Index

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Book SynopsisValuation is a hot topic among life sciences professionals. There is no clear understanding on how to use the different valuation approaches and how to determine input parameters. Some do not value at all, arguing that it is not possible to get realistic and objective numbers out of it. Some claim it to be an art. In the following chapters we will provide the user with a concise val- tion manual, providing transparency and practical insight for all dealing with valuation in life sciences: project and portfolio managers, licensing executives, business developers, technology transfer managers, entrep- neurs, investors, and analysts. The purpose of the book is to explain how to apply discounted cash flow and real options valuation to life sciences p- jects, i.e. to license contracts, patents, and firms. We explain the fun- mentals and the pitfalls with case studies so that the reader is capable of performing the valuations on his own and repeat the theory in the exercises and case studies. The book is structured in five parts: In the first part, the introduction, we discuss the role of the players in the life sciences industry and their p- ticular interests. We describe why valuation is important to them, where they need it, and the current problems to it. The second part deals with the input parameters required for valuation in life sciences, i.e. success rates, costs, peak sales, and timelines.Trade ReviewFrom the reviews:"‘Valuation in Life Sciences: A Practical Guide’ leads readers step by step through the theory of life sciences valuation. … it is an important read for biotech investors. … It is the first book of its kind that combines industry data and valuation theory together with practical advice. It includes valuation techniques and tools that allow investors to pick undervalued biotech stocks." (GEN – genetic engineering news, February, 2007)"Valuation in Life Sciences: A Practical Guide opens up the black box and describes, step by step, a relatively simple procedure for quantitative valuation in life sciences. The book guides the reader through the recommended procedure of quantitative valuation … . This book is recommended to those who would like to acquire a profound understanding of quantitative valuation and use a simple spreadsheet approach of their own cases." (Rudolf Gygax, Nature Biotechnology, Vol. 25 (9), 2007)"This book provides some interesting examples – for business development and licensing executives – of where ROV may be used. … For the general reader and business development executive there is a good explanation of ROV and its applications in life science … . The book may also be of interest to biotechnology company business development executives and university technology transfer officers … . this book is essential reading as it not only provides the mathematical theory but also the applications in different types of deals." (Roger Davies, Business Development & Licensing Journal, Issue 4, 2007)From the reviews of the third edition:“The content and discussion contained in ‘Valuation in Life Sciences’ is excellent. The Swiss authors provide a practical guide to what mathematical tools gives meaningful valuations … . Recommended for anyone planning to be involved in the development of a biotech venture.” (C. Mathews, Amazon, December, 2010)“The authors always keep the necessary rigour to make the book a valuable reference to professionals such as business developers, investment bankers, or analysts. … it an excellent textbook for students as well. … ‘Valuation in Life Sciences’ addresses also the financial beginner with guided and easy-to-understand examples in Excel. I highly recommend the book to everyone in financial biotech.” (Amazon, November, 2009)“This book is an excellent overview of business development valuation and great for those who want to catch up on some techniques and tools. It gives an accurate picture of BD in pharma. For those in the business … it remains a very valuable tool.” (J. Serres, Amazon, March, 2009)Table of ContentsBasics of Valuation.- Valuation in Life Sciences.- Exercises.- Case Studies.

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Book SynopsisClustering is an important unsupervised classification technique where data points are grouped such that points that are similar in some sense belong to the same cluster. Cluster analysis is a complex problem as a variety of similarity and dissimilarity measures exist in the literature.This is the first book focused on clustering with a particular emphasis on symmetry-based measures of similarity and metaheuristic approaches. The aim is to find a suitable grouping of the input data set so that some criteria are optimized, and using this the authors frame the clustering problem as an optimization one where the objectives to be optimized may represent different characteristics such as compactness, symmetrical compactness, separation between clusters, or connectivity within a cluster. They explain the techniques in detail and outline many detailed applications in data mining, remote sensing and brain imaging, gene expression data analysis, and face detection.The book will be useful to graduate students and researchers in computer science, electrical engineering, system science, and information technology, both as a text and as a reference book. It will also be useful to researchers and practitioners in industry working on pattern recognition, data mining, soft computing, metaheuristics, bioinformatics, remote sensing, and brain imaging.Trade ReviewFrom the reviews:“The book focuses on emerging metaheuristic approaches to unsupervised classification, with an emphasis on a symmetry-based definition of similarity. … I found this book very appealing. I also thought of it as very valuable for my preoccupations towards the real-world application of unsupervised classification to medical imaging. I thus believe that, when reading this book, junior as well as experienced researchers will find many new challenging theoretical and practical ideas.” (Catalin Stoean, zbMATH, Vol. 1276, 2014)“The book views clustering as a (multiobjective) optimization problem and tackles it with metaheuristics algorithms. More interestingly, the authors of this book propose the exploitation of the concepts of point and line symmetry to define new distances to be used in clustering techniques. … researchers in the field will surely appreciate it as a good reference on the use of the symmetry notion in clustering.” (Nicola Di Mauro, Computing Reviews, July, 2013)Table of ContentsChap. 1 Introduction.- Chap. 2 Some Single- and Multiobjective Optimization Techniques.- Chap. 3 SimilarityMeasures.- Chap. 4 Clustering Algorithms.- Chap. 5 Point Symmetry Based Distance Measures and their Applications to Clustering.- Chap. 6 A Validity Index Based on Symmetry: Application to Satellite Image Segmentation.- Chap. 7 Symmetry Based Automatic Clustering.- Chap. 8 Some Line Symmetry Distance Based Clustering Techniques.- Chap. 9 Use of Multiobjective Optimization for Data Clustering.- References.- Index.

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Book SynopsisThis textbook is aimed at students of non-specialist courses with computer science components. Special emphasis is placed on the so-called life sciences, such as medical technology, rescue engineering, biotechnology, environmental engineering or process engineering. The textbook is suitable for readers in study and practice who want to get an introduction to computer science. The special feature of this book is the problem-based approach, as well as the exercises designed according to different taxonomy levels.Table of ContentsIntroduction to computer science.- Basics of programming in C++.- Arrays and pointers.- File operations.- Object orientation and inheritance.

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Book SynopsisIn diesem Buch werden dem Leser einführend zentrale Ansätze der Bioinformatik entsprechend dem Fluss der genetischen Information von der Sequenzanalyse vom Virusgenom und seinen Proteinen über die Strukturvorhersage hin zu komplexeren Analysen (Interaktionen mit dem Wirt, Immunsystem) vorgestellt. Proteinnetzwerke, Metabolismus und Signalkaskaden erlauben dem Virus, eine hochgefährliche Infektion im Menschen zu erzeugen. Die Bioinformatik leistet wertvolle Hilfestellung bei der Diagnose, der Suche nach Behandlungsmöglichkeiten und vor allem bei der Herstellung von Impfstoffen und dem Vorhersehen des Pandemieverlaufs.Der Inhalt Bioinformatik ist einfach und schnell anzuwenden Erste Detailanalysen (Sequenzen, Proteine, Gene) Analyse von Protein-Netzwerken Bioinformatik in der Infektionsbiologie und medizinische Implikationen Bioinformatik und Covid19 – ein globales Phänomen Anhang: Nützliche Webressourcen und Literaturstellen Die Zielgruppen Studenten der Biologie und Medizin, die einen ersten Einblick in die Bioinformatik haben möchten Allgemeines Publikum Table of ContentsBioinformatik ist einfach und schnell anzuwenden.- Erste Detailanalysen.- Analyse von Protein-Netzwerken.- Infektionsbiologie und medizinische Implikationen.- Nachspiel: Wie stark wartet die Welt auf die Ergebnisse der Bioinformatik zu Covid19?.

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Book SynopsisDieses Buch bietet durch instruktive Strichzeichnungen und erläuternde Kurztexte zu wesentlichen Körpermerkmalen wirbelloser Tiere einen einfachen und sicheren Einstieg in deren Bestimmung.Kurze Einführungen in 20 Tiergruppen (und Gallen) informieren über Körperbau, Lebensweise, Lebensräume, Beobachtungs- und Sammelmöglichkeiten. Einbezogen sind Formen und teils auch deren Larven an Land und im Süßwasser, die sich ohne Spezialkenntnisse bis zur Art, bei schwierigen Taxa auch nur bis zur Gattung oder Familie bestimmen lassen. Anhand der skizzierten Merkmale lassen sich über dichotome oder multiple Entscheidungsschritte über 2700 Arten und Gattungen bestimmen. Das Register erschließt alle in den Bildtafeln genannten, wissenschaftlichen und gebräuchlichen deutschen Namen sowie häufige Synonyme. Das Literaturverzeichnis enthält die wichtigsten weiterführenden Bestimmungswerke zu wirbellosen Tieren und zu den einzelnen Tiergruppen.In der 8. Neuauflage wurden bei einem Drittel aller Bildtafeln etliche Namen aktualisiert, neue Skizzen eingefügt, Bestimmungsgänge verbessert und weitere häufig gewordene invasive Arten aufgenommen. Insgesamt 36 Tafeln wurden völlig neu bearbeitet, neben einer Makrozoobenthos-Übersicht noch Planarien, Zecken (♂♂), Fluss- und Flohkrebse, Libellen, Ohrwürmer, Schaben, Blattläuse (an Laubgehölzen) sowie Netzflügler. Für Studenten und Schüler, Gutachter im Umwelt- und Hygienebereich, Tierfotografen sowie Naturfreunde lässt sich mit diesem praktischen Bestimmungsbuch auf einfache Weise eine große Zahl wirbelloser Tiere sicher einordnen und ansprechen, sowohl unmittelbar in deren Lebensräumen als auch in Fallenfängen und Sammlungen. Table of Contents

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Book SynopsisThis book is a practical guide for biologists who use multiple sequence alignments (MSAs) for their data analysis and are looking for a comprehensive overview of the many different programs. Despite their important role in data analysis, there is uncertainty among researchers about exactly how MSA programs work - not to mention how and why the different analyzes lead to different results. Which program is the right one for evaluating my data and how can I ensure that I have drawn all relevant findings from the alignments? This book offers helpful explanations and background information without requiring extensive bioinformatics knowledge and slowly introduces the reader to the topic.In the first part of the book, the possible fields of application as well as the formats that are usually produced by MSA programs are described in detail. The central algorithms as well as the internal processes of the most common MSA programs of the past and the present are also explained in an uncomplicated manner in greater detail. The second part of the book is a detailed, data-based comparison between MSA programs, which is intended to help you decide which program to use for your next alignment. Table of ContentsI Background.- 1 Multiple sequence alignments: an introduction.- 2 How do MSA programs work?.- 3 Overview of current MSA programs.- II Which MSA algorithm is right for me?.- 4 Details for analyzing the programs.- 5 Decision support..- Glossary.- Literature.- Index.

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Book SynopsisThis book offers a gripping introduction to the fastest growing field of biology with easy-to-follow examples and a well-prepared appendix for the reader to cook up and experience everything right away.The book gets the reader started with the basics, such as how to easily find sequence information and then analyze it. In further chapters, the authors go into the various analysis options from RNA, DNA and proteins to entire metabolic pathways. Exciting examples from biology are chosen in each chapter to illustrate the analysis. Each chapter concludes with an exercise section that immediately puts what has been learned to use.The subject of this book is a must for any biology student, whether undergraduate or graduate, as bioinformatics is now unearthing amazing insights into the molecular basis of all living things. Computer science students and other students from related sciences will get a good introduction to bioinformatics, as biology and current topics (e.g. AI) are systematically introduced step by step alongside the software.Discover the key to life together with the authors and learn to understand the language of life. This book is a translation of the original German 2nd edition Bioinformatik by Thomas Dandekar and Meik Kunz, published by Springer-Verlag GmbH Germany, part of Springer Nature in 2021. The translation was done with the help of artificial intelligence (machine translation by the service DeepL.com). A subsequent human revision was done primarily in terms of content, so that the book will read stylistically differently from a conventional translation. Springer Nature works continuously to further the development of tools for the production of books and on the related technologies to support the authors.Table of ContentsI How does bioinformatics work?.- 1 Sequence analysis: deciphering the language of life.- 2 Magic RNA.- 3 Genomes - molecular maps of living organisms.- 4 Modeling metabolism and finding new antibiotics.- 5 Systems biology and uncovering the causes of disease. II How do I understand bioinformatics?"- 6 Superfast sequence comparisons identify which molecules are present.- 7 Better understand signaling cascades by measuring encoded information.- 8 When does a computer stop computing?"- 9 Complex systems behave in fundamentally similar ways.- 10 Better compare evolution with a computer.- 11 Design principles of a cell. III What is the magical, fascinating thing about bioinformatics?.- 12 Life is always developing new information in dialogue with the environment.- 13 Life is always inventing new levels of language.- 14 We can think about ourselves - the computer cannot.- 15 How is our own, extremely powerful brain built?.- 16 Bioinformatics connects life with the universe and all the rest.- 17 Conclusion. 17 Concluding remarks and summary.- IV Glossary, tutorial, solutions and web links.- 18 Glossary.- 19 Tutorial: an overview of important databases and programs.- 20 Solutions to the exercises.- Appendix: overview of important databases and programs and their general use.- Index.

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Book SynopsisWhat actually is a p-value for? And what is a significant result? This book answers such questions by providing a compact introduction to inferential statistics. Our major focus is on the logic of inferential statistics and hypothesis testing: We cover the logic behind statistical tests, we then walk through the most common procedures (t-test, analysis of variance with and without repeated measures, correlation/regression) and discuss pitfalls of data analysis. The book thus helps developing a solid understanding of how common test procedures work, and how to interpret their results correctly. Hands-on examples from everyday research – including exemplary calculations with the programs SPSS and R – supplement each chapter. In addition to classical methods, we briefly discuss recent developments in psychological research methods.This book is a translation of the original German 3rd edition of “Inferenzstatistik Verstehen” by Markus Janczyk and Roland Pfister. It is based on an AI-powered machine translation (by the service DeepL.com), with thorough follow-up editing by both authors.Table of ContentsIntroduction and descriptive statistics.- Basics of inferential statistics 1: random variables.- Basics of inferential statistics 2: population and parameter estimation.- Hypothesis testing and significance.- Difference hypotheses with a maximum of two groups: t-tests. Confidence intervals.- Error types, effect size and power.- Single factor analysis of variance.- Multifactorial analysis of variance.- Analysis of variance with repeated measures.- Correlation hypotheses: Correlation and regression.- Concluding remarks.

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Book SynopsisThis book presents models written as partial differential equations and originating from various questions in population biology, such as physiologically structured equations, adaptive dynamics, and bacterial movement. Its purpose is to derive appropriate mathematical tools and qualitative properties of the solutions. The book further contains many original PDE problems originating in biosciences.Table of ContentsFrom differential equations to structured population dynamics.- Adaptive dynamics; an asymptotic point of view.- Population balance equations: the renewal equation.- Population balance equations: size structure.- Cell motion and chemotaxis.- General mathematical tools.

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Book SynopsisThis book delves into various applications and tools of bioinformatics in a range of fields, including agriculture, corals, structural bioinformatics, data mining, text mining, medicinal plants, antibiotics, protein structure prediction, drug design, gene expression, micro-arrays, proteomics, molecular phylogenetics, artificial neural networks, plant systems biology, molecular modeling, homology modeling, bio-efficacy of indigenous bacillus through in-silico approach, and fresh aquaculture and fisheries. It also covers topics such as pesticides and insecticides, database and tool development in relevant areas, and would be of great utility to individuals working in the fields of agricultural biotechnology, bioinformatics, computer science, and applied statistics.

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Book SynopsisThis book focuses on a variety of bioinformatics tools and applications across several fields, including agriculture, corals, structural bioinformatics, data and text mining, medicinal plants, antibiotics, protein structure prediction, drug design, gene expression, microarrays, proteomics, molecular phylogenetics, rough sets for protein structural class prediction, artificial neural networks for predicting amino acid levels, plant systems biology, molecular modeling, homology modeling, bioefficacy of indigenous bacillus through in silico approach, and fresh aquaculture and fisheries. This book would be of value to individuals working in agricultural biotechnology, bioinformatics, computer science, and applied statistics. Rephrased with a formal tone.

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Book SynopsisIn the present thesis we develop new strategies concerning the use of lanthanide cations as spectroscopic probes for the study of molecular structures in solution. A widespread interest for lanthanides is mainly centered in two large fields: organic synthesis and clinical practice. Systems containing lanthanides enjoy a very favorable situation, since these ions feature high coordination numbers, which assure rich binding chemistry, and at the same time they possess the right spectroscopic properties to monitor it. The present thesis develops the potentialities of electronic spectroscopy of lanthanide systems in solution. We point out and overcome the drawbacks which have mainly hampered this kind of study so far, namely: a sensivity problem, an instrumental problem and a calibration problem.

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Book SynopsisSensory experience can dynamically modify both the anatomy and function of the brain. In particular, neurons can modify their connections in response to enviromental stimuli. This process, generally referred to as “neuronal plasticity”, is the basis of learning and memory processes in the brain. Which are the bases of neuronal plasticity? That is, how can environmental factors and sensory experience modify the connections between neurons? Neurotrophic factors of the Nerve Growth Factor (NGF) family are known to finely regulate the development and maintenance of synaptic connections in the PNS. The results obtained by the group of Maffei firstly suggested the hypothesis that neurotrophic factors could play a key role in the plasticity of the mammalian visual system. The purpose of this thesis is to give a general overview about the recent advances in the field of neurotrophine-regulated plasticity of the mammalian visual system.

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Book SynopsisNeuronal plasticity is the term generally used to describe a great variety of changes in neuronal structure and functions, in particular activity-dependent, prolonged functional changes, accompanied by corresponding biochemical and possibly morphological alterations. The first insights about neuronal plasticity have been obtained on simple forms of life. Today, many areas in the mammalian central nervous system are under investigation, in particular the cortex and the hippocampus. In these areas, neuronal plasticity is considered to be at the basis of learning and memory. The study of brain plasticity in sensory systems has been particularly fruitful, because these systems can be experimentally manipulated in a very precise manner by changes in the sensory imput.

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Book SynopsisAgro-informatics is the application in agriculture with innovative ideas, techniques and scientific knowledge to expand the horizons of the Computer Science. The book contains the details about the information technology applied to management and analysis of agricultural data The book covers the diverse areas ranging from artificial intelligence, artificial neural networks, decision support system, expert system, geographic information system, information system related to agriculture, genetic algorithm, programming language with backend tool to develop softwares The book contains fifteen s that highlight and discuss the various dimensions of agro-informatics. It is hoped that the book will provide the basic and fundamental knowledge of understanding the concepts of Bioinformatics. This book is prepared, taking into consideration the changing needs of the undergraduate curricula of various universities involved in offering courses on agro-informatics The book will also be a guide for the researchers The book would also provide the required computer knowledge to the students of State Agricultural Universities and other ICAR Institutions to sharpen their understanding of agro-informatics.Table of Contents01. Introduction to Agroinformatics 02. Agriculture Information System 03. Farm Management System 04. Management Information System 05. Geographic Information System 06. Artificial Intelligence 07. Artificial Neural Networks 08. Expert Systems 09. Decision Support System DSS 10. Genetic Algorithms 11. Programming Language - Visual Basic 12. Database Management System 13 . Agricultural Databases, Technical Report and Conference Reports 14. Web Portal 15. Introduction to Bioinformatics

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Book SynopsisThe book deals with various tools and applications of bioinformatics in the fields of: o agriculture, corals, structural bioinformatics, data-mining, text-mining; o medicinal plants, antibiotics, protein structure prediction, drug design; o gene expression, micro-arrays, proteomics, molecular phylogenic location of the Indian Liver Fluke, rough sets to predict protein structural class; o artificial neural networks for prediction of amino acids levels, plant systems biology, molecular modeling, homology modeling, bio-efficacy of indigenous bacillus through in-silico approach; o fresh aquaculture and fisheries, pesticides and insecticides, databases and tools development in the relevant area. The book would be of much use to the person working in the field of agricultural biotechnology, bioinformatics, computer science and applied statistics. This can act as a book for M.Sc, M.Tech and Ph.D students of and the faculty of Bioinformatics/Biotechnologists.Table of Contents01. Application of Bioinformatics in Agriculture D. Velmurugan 02. Statistical Data Mining-Concepts, Tools and Techniques for Bioinformatics Ravi R. Saxena, Ritu R. Saxena, Akash Solanki and M.L. Lakhera 03. Prediction of 3D Structure of Proteins Using Artificial Neural Networks K. Meena 04. A Genomic Approach to Study the Insect Mitochondrial Evolution by Noncoding LSU and SSU rRNA 41S. Gifta Lorraine, Christy Jancy Joy P., Arul Samraj D. and Priyakumari Joyce C. 05. Analysis of Microarray Gene Expression Data M. Balakrishnan, R.C. Srivastava and M. Ramachandran 06. A Novel Sequence Encoding Method for Searching Rareness Among Consensus DNA Sequences K. Meena, K. Menaka, T.V. Sundar and K. R. Subramanian 07. Statistical Methods for Genomic Sequence and Microarray Analysis A.K. Roy and S.R. Martha 08. Significance of Insect Genomics in Agro Ecosystems R.W. Alexander Jesudasan09. Bioinformatics Tools in Fish Molecular Modeling Grinson George, K.Sarma, S. Dam Roy and Mukunda Goswamy10. Structural Bioinformatics Goals and Challenges Mayank Pokhriyal and M. Balakrishnan 11. Database for Animal Genetic Resources of A &N IslandsM. Balakrishnan, S. Jeyakumar, R.C. Srivastava, Mayank Pokhriyal and Soma Mondal 12. A Database for Medicinal Plants used in Treatment of Asthma K. Balaji, M. Rajadurai, G. Vidhya, A. Krithika, E. Hudson, Vidya Murali, M. Ramya, Anusha Bhaskar and V. Stanley 13. In-silico Determination of Potential Drug Target for Curing Meningococcal Disease- Bioinformatics Study On Penicillin- Binding Proteins Vijay Tripathi, Dwijendra Gupta and Navita Srivastava 14. Text Mining: Potential Applications in Bioinformatics M. Balakrishnan, R.C. Srivastava, S.K. Zamir Ahmed and Subhash Chand 15. Diversity and Antibacterial Activity of Coral Associated Actinomycetes P. Nithyanand, S. Manju and S. Karutha Pandian 16. Decision Tree and its Application in Bioinformatics Rajni Jain and Amarendra Kumar Mishra 17. Database for Algae Resources in Andaman and Nicobar Islands M. Balakrishnan 18. Bioinformatics of Natural Antibiotics S. Rajarajan, M. Yogambal, K. Sangeetha 19. PhytopathoSys v1.0 A Phytopathology Information System M. Balakrishnan, R.C. Srivastava, Michael Imanual Jesse and M. Ramachandran 20. Multiple Gene Expression Profiles of Chemically Induced Parkinson Disease: Implication in Neuroprotection Mechanism Offered by Nicotine and Caffeine Kavita Singh, M.P. Singh and M. Balakrishnan 21. Development of Databases on Freshwater Aquaculture A.K. Roy and Nibedita Jena 22. Proteomics and Bioinformatics A. Subash Chandira Bose, R. Venkateshwaran and M. Balakrishnan23. Data Mining and its Applications in Bioinformatics Soma Mondal and M. Balakrishnan 24. Molecular Phylogenic Location of the Indian Liver Fluke, Fasciola (Trematoda: Fasciolidae) Based on The Ribosomal Internal Transcribed Spacer Regions P. K. Prasad, V. Tandon, D.K. Biswal, L.M. Goswami and A. Chatterjee 25. Prediction of Amino Acid Levels in Protein Sequences Using Artificial Neural Networks K.Meena and M. Manimekalai 26. Applying New Data Mining Method of Rough Sets to Predict Protein Structural Class K. Meena and M. Durairaj 27. Plant Systems Biology G. Ramesh Kumar, CP Rajadurai and M. Ramachandran 28. Bio-efficacy of Indigenous Bacillus thuringiensis LDC-9 Against Insect Pest and its Characterization through In-silico Approach R. Shenbagarathai and A. Mahalakshmi 29. Molluscan Resources and Its Management Measures in Andaman & Nicobar Islands S.N. Sethi, M. Balakrishnan, S. Chand and B.Varghese

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Book SynopsisThe book is mainly about hybrid systems with continuous/discrete-time dynamics. The major part of the book consists of the theory of equations with piece-wise constant argument of generalized type. The systems as well as technique of investigation were introduced by the author very recently. They both generalized known theory about differential equations with piece-wise constant argument, introduced by K. Cook and J. Wiener in the 1980s. Moreover, differential equations with fixed and variable moments of impulses are used to model real world problems. We consider models of neural networks, blood pressure distribution and a generalized model of the cardiac pacemaker. All the results of the manuscript have not been published in any book, yet. They are very recent and united with the presence of the continuous/discrete dynamics of time. It is of big interest for specialists in biology, medicine, engineering sciences, electronics. Theoretical aspects of the book meet very strong expectations of mathematicians who investigate differential equations with discontinuities of any type.Trade ReviewFrom the reviews:“Hybrid systems are a recent concept in dynamical systems theory and have important and extensive applications. … The present book generalizes the concept of differential equations with piecewise constant argument by considering a more general type of equations and develops new methodological approaches to explore those challenging systems. … This book is well written and readable and will be extremely useful not only to expert readers but also to graduate and advanced undergraduate students.” (Meng Fan, Mathematical Reviews, January, 2013)Table of Contents1. Introduction.- 2. Linear and quasi-linear systems with piecewise constant argument.- 3. The reduction principle for systems with piecewise constant argument.- 4. The small parameter and differential equations with piecewise constant argument.- 5. Stability.- 6. The state-dependent piecewise constant argument.- 7. Almost periodic solutions.- 8. Stability of neural networks.- 9. The blood pressure distribution.- 10. Integrate-and-fire biological oscillators.

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Book SynopsisFixing Your Damaged and Incorrect Genes is a book about a well-established biological process called DNA REPAIR. The book describes the multiple and varied biochemical strategies by which damaged or incorrect nucleotides are removed from DNA or are corrected. The book includes multiple figures of notable past and present scientists in the field. The book is uniquely focused on an audience of non-biologists and is written in simple language with minimal use of technical terms. It contains an extensive glossary that provides explanations of key words that readers are encouraged to refer to as they read. Fixing Your Damaged and Incorrect Genes is unique, there being no previously published books for non-biologists on the topic of DNA repair.

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Book SynopsisThis is an introductory text and laboratory manual to be used primarily in undergraduate courses. It is also useful for graduate students and research scientists who require an introduction to the theory and methods of nanopore sequencing. The book has clear explanations of the principles of this emerging technology, together with instructional material written by experts that describes how to use a MinION nanopore instrument for sequencing in research or the classroom.At Harvard University the book serves as a textbook and lab manual for a university laboratory course designed to intensify the intellectual experience of incoming undergraduates while exploring biology as a field of concentration. Nanopore sequencing is an ideal topic as a path to encourage students about the range of courses they will take in Biology by pre-emptively addressing the complaint about having to take a course in Physics or Maths while majoring in Biology. The book addresses this complaint by concretely demonstrating the range of topics — from electricity to biochemistry, protein structure, molecular engineering, and informatics — that a student will have to master in subsequent courses if he or she is to become a scientist who truly understands what his or her biology instrument is measuring when investigating biological phenomena.

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Book SynopsisBreakthroughs in high-throughput genome sequencing and high-performance computing technologies have empowered scientists to decode many genomes including our own. Now they have a bigger ambition: to fully understand the vast diversity of microbial communities within us and around us, and to exploit their potential for the improvement of our health and environment. In this new field called metagenomics, microbial genomes are sequenced directly from the habitats without lab cultivation. Computational metagenomics, however, faces both a data challenge that deals with tens of tera-bases of sequences and an algorithmic one that deals with the complexity of thousands of species and their interactions.This interdisciplinary book is essential reading for those who are interested in beginning their own journey in computational metagenomics. It is a prism to look through various intricate computational metagenomics problems and unravel their three distinctive aspects: metagenomics, data engineering, and algorithms. Graduate students and advanced undergraduates from genomics science or computer science fields will find that the concepts explained in this book can serve as stepping stones for more advanced topics, while metagenomics practitioners and researchers from similar disciplines may use it to broaden their knowledge or identify new research targets.

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