{"product_id":"parallel-computing-for-bioinformatics-and-computational-biology-models-enabling-technologies-and-case-studies-55-wiley-series-on-parallel-and-distributed-computing-9780471718482","title":"Parallel Computing for Bioinformatics and","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eParallel Computing for Bioinformatics is the first book to deal with the topic of parallel computing and bioinformatics. Written by renowned experts and well-reputed researchers in this emerging field, it provides an opportunity for researchers to explore the rich and complex subject of ?Bioinformatics?.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003e\"…clearly written and understandable…researchers and students in the related areas will find the style and format familiar and the content valuable.\" (\u003ci\u003eE-STREAMS\u003c\/i\u003e, September 2007)  \u003cp\u003e\"…a building block on computational biology concepts to help researchers and students work on more innovative ideas.\" (\u003ci\u003eIEEE Distributed Systems Online\u003c\/i\u003e, March 2007)\u003c\/p\u003e \u003cp\u003e\"…a good overview of the current state of computing in these areas.\" (\u003ci\u003eCHOICE\u003c\/i\u003e, November 2006)\u003c\/p\u003e \u003cp\u003e\"…this book presents researchers in computational biology, bioinformatics, mathematics, statistics, and computer science with the opportunity to explore this interdisciplinary research area…\" (\u003ci\u003eComputing Reviews.com\u003c\/i\u003e, September 27, 2006)\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cb\u003ePreface.\u003c\/b\u003e  \u003cp\u003e\u003cb\u003eContributors.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAcknowledgments.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART I: ALGORITHMS AND MODELS.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Parallel and Evolutionary Approaches to Computational Biology\u003c\/b\u003e (\u003ci\u003eNouhad J. Rizk\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e1.1 Introduction.\u003c\/p\u003e \u003cp\u003e1.2 Bioinformatics.\u003c\/p\u003e \u003cp\u003e1.3 Evolutionary Computation Applied to Computational Biology.\u003c\/p\u003e \u003cp\u003e1.4 Conclusions.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Parallel Monte Carlo Simulation of HIV Molecular Evolution in Response to Immune Surveillance\u003c\/b\u003e (\u003ci\u003eJack da Silva\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e2.1 Introduction.\u003c\/p\u003e \u003cp\u003e2.2 The Problem.\u003c\/p\u003e \u003cp\u003e2.3 The Model.\u003c\/p\u003e \u003cp\u003e2.4 Parallelization with MPI.\u003c\/p\u003e \u003cp\u003e2.5 Parallel Random Number Generation.\u003c\/p\u003e \u003cp\u003e2.6 Preliminary Simulation Results.\u003c\/p\u003e \u003cp\u003e2.7 Future Directions.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Differential Evolutionary Algorithms for In Vivo Dynamic Analysis of Glycolysis and Pentose Phosphate Pathway in\u003c\/b\u003e \u003cb\u003e\u003ci\u003eEscherichia coli\u003c\/i\u003e\u003c\/b\u003e (\u003ci\u003eChristophe Chassagnole\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e3.1 Introduction.\u003c\/p\u003e \u003cp\u003e3.2 Mathematical Model.\u003c\/p\u003e \u003cp\u003e3.3 Estimation of the Parameters of the Model.\u003c\/p\u003e \u003cp\u003e3.4 Kinetic Parameter Estimation by DE.\u003c\/p\u003e \u003cp\u003e3.5 Simulation and Results.\u003c\/p\u003e \u003cp\u003e3.6 Stability Analysis.\u003c\/p\u003e \u003cp\u003e3.7 Control Characteristic.\u003c\/p\u003e \u003cp\u003e3.8 Conclusions.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Compute-Intensive Simulations for Cellular Models\u003c\/b\u003e (\u003ci\u003eK. Burrage\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e4.1 Introduction.\u003c\/p\u003e \u003cp\u003e4.2 Simulation Methods for Stochastic Chemical Kinetics.\u003c\/p\u003e \u003cp\u003e4.3 Aspects of Biology— Genetic Regulation.\u003c\/p\u003e \u003cp\u003e4.4 Parallel Computing for Biological Systems.\u003c\/p\u003e \u003cp\u003e4.5 Parallel Simulations.\u003c\/p\u003e \u003cp\u003e4.6 Spatial Modeling of Cellular Systems.\u003c\/p\u003e \u003cp\u003e4.7 Modeling Colonies of Cells.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Parallel Computation in Simulating Diffusion and Deformation in Human Brain\u003c\/b\u003e (\u003ci\u003eNing KangI0.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction.\u003c\/p\u003e \u003cp\u003e5.2 Anisotropic Diffusion Simulation in White Matter Tractography.\u003c\/p\u003e \u003cp\u003e5.3 Brain Deformation Simulation in Image-Guided Neurosurgery.\u003c\/p\u003e \u003cp\u003e5.4 Summary.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART II: SEQUENCE ANALYSIS AND MICROARRAYS.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Computational Molecular Biology\u003c\/b\u003e (\u003ci\u003eAzzedine Boukerche\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e6.1 Introduction.\u003c\/p\u003e \u003cp\u003e6.2 Basic Concepts in Molecular Biology.\u003c\/p\u003e \u003cp\u003e6.3 Global and Local Biological Sequence Alignment.\u003c\/p\u003e \u003cp\u003e6.4 Heuristic Approaches for Biological Sequence Comparison.\u003c\/p\u003e \u003cp\u003e6.5 Parallel and Distributed Sequence Comparison.\u003c\/p\u003e \u003cp\u003e6.6 Conclusions.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Special-Purpose Computing for Biological Sequence Analysis\u003c\/b\u003e (\u003ci\u003eBertil Schmidt\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e7.1 Introduction.\u003c\/p\u003e \u003cp\u003e7.2 Hybrid Parallel Computer.\u003c\/p\u003e \u003cp\u003e7.3 Dynamic Programming Communication Pattern.\u003c\/p\u003e \u003cp\u003e7.4 Performance Evaluation.\u003c\/p\u003e \u003cp\u003e7.5 FutureWork and Open Problems.\u003c\/p\u003e \u003cp\u003e7.6 Tutorial.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Multiple Sequence Alignment in Parallel on a Cluster ofWorkstations\u003c\/b\u003e (\u003ci\u003eAmitava Datta\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e8.1 Introduction.\u003c\/p\u003e \u003cp\u003e8.2 CLUSTALW.\u003c\/p\u003e \u003cp\u003e8.3 Implementation.\u003c\/p\u003e \u003cp\u003e8.4 Results.\u003c\/p\u003e \u003cp\u003e8.5 Conclusion.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Searching Sequence Databases Using High-Performance BLASTs\u003c\/b\u003e (\u003ci\u003eXue Wu\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e9.1 Introduction.\u003c\/p\u003e \u003cp\u003e9.2 Basic Blast Algorithm.\u003c\/p\u003e \u003cp\u003e9.3 Blast Usage and Performance Factors.\u003c\/p\u003e \u003cp\u003e9.4 High Performance BLASTs.\u003c\/p\u003e \u003cp\u003e9.5 Comparing BLAST Performance.\u003c\/p\u003e \u003cp\u003e9.6 UMD-BLAST.\u003c\/p\u003e \u003cp\u003e9.7 Future Directions.\u003c\/p\u003e \u003cp\u003e9.8 RelatedWork.\u003c\/p\u003e \u003cp\u003e9.9 Summary.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Parallel Implementations of Local Sequence Alignment: Hardware and Software\u003c\/b\u003e (\u003ci\u003eVipin Chaudhary\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e10.1 Introduction.\u003c\/p\u003e \u003cp\u003e10.2 Sequence Alignment Primer.\u003c\/p\u003e \u003cp\u003e10.3 Smith–Waterman Algorithm.\u003c\/p\u003e \u003cp\u003e10.4 FASTA.\u003c\/p\u003e \u003cp\u003e10.5 BLAST.\u003c\/p\u003e \u003cp\u003e10.6 HMMER — Hidden Markov Models.\u003c\/p\u003e \u003cp\u003e10.7 ClustalW.\u003c\/p\u003e \u003cp\u003e10.8 Specialized Hardware: FPGA.\u003c\/p\u003e \u003cp\u003e10.9 Conclusion.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Parallel Computing in the Analysis of Gene Expression Relationships\u003c\/b\u003e (\u003ci\u003eRobert L. Martino\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e11.1 Significance of Gene Expression Analysis.\u003c\/p\u003e \u003cp\u003e11.2 Multivariate Gene Expression Relations.\u003c\/p\u003e \u003cp\u003e11.3 Classification Based on Gene Expression.\u003c\/p\u003e \u003cp\u003e11.4 Discussion and Future Directions.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Assembling DNA Fragments with a Distributed Genetic Algorithm\u003c\/b\u003e (\u003ci\u003eGabriel Luque\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e12.1 Introduction.\u003c\/p\u003e \u003cp\u003e12.2 DNA Fragment Assembly Problem.\u003c\/p\u003e \u003cp\u003e12.3 DNA Fragment Assembly Using the Sequential GA.\u003c\/p\u003e \u003cp\u003e12.4 DNA Fragment Assembly Problem Using the Parallel GA.\u003c\/p\u003e \u003cp\u003e12.5 Experimental Results.\u003c\/p\u003e \u003cp\u003e12.6 Conclusions.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 A Cooperative Genetic Algorithm for Knowledge Discovery in Microarray Experiments\u003c\/b\u003e (\u003ci\u003eMohammed Khabzaoui\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e13.1 Introduction.\u003c\/p\u003e \u003cp\u003e13.2 Microarray Experiments.\u003c\/p\u003e \u003cp\u003e13.3 Association Rules.\u003c\/p\u003e \u003cp\u003e13.4 Multi-Objective Genetic Algorithm.\u003c\/p\u003e \u003cp\u003e13.5 Cooperative Multi-Objective Genetic Algorithm (PMGA).\u003c\/p\u003e \u003cp\u003e13.6 Experiments.\u003c\/p\u003e \u003cp\u003e13.7 Conclusion.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART III: PHYLOGENETICS.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Parallel and Distributed Computation of Large Phylogenetic Trees\u003c\/b\u003e (\u003ci\u003eAlexandros Stamatakis\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e14.1 Introduction.\u003c\/p\u003e \u003cp\u003e14.2 Maximum Likelihood.\u003c\/p\u003e \u003cp\u003e14.3 State-of-the-Art ML Programs.\u003c\/p\u003e \u003cp\u003e14.4 Algorithmic Solutions in RAxML-III.\u003c\/p\u003e \u003cp\u003e14.5 HPC Solutions in RAxML-III.\u003c\/p\u003e \u003cp\u003e14.6 Future Developments.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 Phylogenetic Parameter Estimation on COWs\u003c\/b\u003e  (\u003ci\u003eEkkehard Petzold\u003c\/i\u003e).\u003cbr\u003e \u003c\/p\u003e \u003cp\u003e15.1 Introduction.\u003c\/p\u003e \u003cp\u003e15.2 Phylogenetic Tree Reconstruction using Quartet Puzzling.\u003c\/p\u003e \u003cp\u003e15.3 Hardware, Data, and Scheduling Algorithms.\u003c\/p\u003e \u003cp\u003e15.4 Parallelizing PEst.\u003c\/p\u003e \u003cp\u003e15.5 Extending Parallel Coverage in PEst.\u003c\/p\u003e \u003cp\u003e15.6 Discussion.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e16 High-Performance Phylogeny Reconstruction Under Maximum Parsimony\u003c\/b\u003e (\u003ci\u003eTiffani L. Williams\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e16.1 Introduction.\u003c\/p\u003e \u003cp\u003e16.2 Maximum Parsimony.\u003c\/p\u003e \u003cp\u003e16.3 Exact MP: Parallel Branch and Bound.\u003c\/p\u003e \u003cp\u003e16.4 MP Heuristics: Disk-Covering Methods.\u003c\/p\u003e \u003cp\u003e16.5 Summary and Open Problems.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART IV: PROTEIN FOLDING.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e17 Protein Folding with the Parallel Replica Exchange Molecular Dynamics Method\u003c\/b\u003e (\u003ci\u003eRuhong Zhou\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e17.1 Introduction.\u003c\/p\u003e \u003cp\u003e17.2 REMD Method.\u003c\/p\u003e \u003cp\u003e17.3 Protein Folding with REMD.\u003c\/p\u003e \u003cp\u003e17.4 Protein Structure Refinement with REMD.\u003c\/p\u003e \u003cp\u003e17.5 Summary.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e18 High-Performance Alignment Methods for Protein Threading\u003c\/b\u003e (\u003ci\u003eR. Andonov\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e18.1 Introduction.\u003c\/p\u003e \u003cp\u003e18.2 Formal Definition.\u003c\/p\u003e \u003cp\u003e18.3 Mixed Integer Programming Models.\u003c\/p\u003e \u003cp\u003e18.4 Divide-and-Conquer Technique.\u003c\/p\u003e \u003cp\u003e18.5 Parallelization.\u003c\/p\u003e \u003cp\u003e18.6 Future Research Directions.\u003c\/p\u003e \u003cp\u003e18.7 Conclusion.\u003c\/p\u003e \u003cp\u003e18.8 Summary.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e19 Parallel Evolutionary Computations in Discerning Protein Structures\u003c\/b\u003e (\u003ci\u003eRichard O. Day\u003c\/i\u003e).\u003cbr\u003e \u003c\/p\u003e \u003cp\u003e19.1 Introduction.\u003c\/p\u003e \u003cp\u003e19.2 PSP Problem.\u003c\/p\u003e \u003cp\u003e19.3 Protein Structure Discerning Methods.\u003c\/p\u003e \u003cp\u003e19.4 PSP Energy Minimization EAs.\u003c\/p\u003e \u003cp\u003e19.5 PSP Parallel EA Performance Evaluation.\u003c\/p\u003e \u003cp\u003e19.6 Results and Discussion.\u003c\/p\u003e \u003cp\u003e19.7 Conclusions and Suggested Research.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART V: PLATFORMS AND ENABLING TECHNOLOGIES.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e20 A Brief Overview of Grid Activities for Bioinformatics and Health Applications\u003c\/b\u003e (\u003ci\u003eAli Al Mazari\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e20.1 Introduction.\u003c\/p\u003e \u003cp\u003e20.2 Grid Computing.\u003c\/p\u003e \u003cp\u003e20.3 Bioinformatics and Health Applications.\u003c\/p\u003e \u003cp\u003e20.4 Grid Computing for Bioinformatics and Health Applications.\u003c\/p\u003e \u003cp\u003e20.5 Grid Activities in Europe.\u003c\/p\u003e \u003cp\u003e20.6 Grid Activities in the United Kingdom.\u003c\/p\u003e \u003cp\u003e20.7 Grid Activities in the USA.\u003c\/p\u003e \u003cp\u003e20.8 Grid Activities in Asia and Japan.\u003c\/p\u003e \u003cp\u003e20.9 International Grid Collaborations.\u003c\/p\u003e \u003cp\u003e20.10 International Grid Collaborations.\u003c\/p\u003e \u003cp\u003e20.11 Conclusions and Future Trends.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e21 Parallel Algorithms for Bioinformatics\u003c\/b\u003e (\u003ci\u003eShahid H. Bokhari\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e21.1 Introduction.\u003c\/p\u003e \u003cp\u003e21.2 Parallel Computer Architecture.\u003c\/p\u003e \u003cp\u003e21.3 Bioinformatics Algorithms on the Cray MTA System.\u003c\/p\u003e \u003cp\u003e21.4 Summary.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e22 Cluster and Grid Infrastructure for Computational Chemistry and Biochemistry\u003c\/b\u003e (\u003ci\u003eKim K. Baldridge\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e22.1 Introduction.\u003c\/p\u003e \u003cp\u003e22.2 GAMESS Execution on Clusters.\u003c\/p\u003e \u003cp\u003e22.3 Portal Technology.\u003c\/p\u003e \u003cp\u003e22.4 Running GAMESS with Nimrod Grid-Enabling Infrastructure.\u003c\/p\u003e \u003cp\u003e22.5 Computational ChemistryWorkflow Environments.\u003c\/p\u003e \u003cp\u003e22.6 Conclusions.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e23 DistributedWorkflows in Bioinformatics\u003c\/b\u003e (\u003ci\u003eArun Krishnan\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e23.1 Introduction.\u003c\/p\u003e \u003cp\u003e23.2 Challenges of Grid Computing.\u003c\/p\u003e \u003cp\u003e23.3 Grid Applications.\u003c\/p\u003e \u003cp\u003e23.4 Grid Programming.\u003c\/p\u003e \u003cp\u003e23.5 Grid Execution Language.\u003c\/p\u003e \u003cp\u003e23.6 GUI-BasedWorkflow Construction and Execution.\u003c\/p\u003e \u003cp\u003e23.7 Case Studies.\u003c\/p\u003e \u003cp\u003e23.8 Summary.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e24 Molecular Structure Determination on a Computational and Data Grid\u003c\/b\u003e (\u003ci\u003eRuss Miller\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e24.1 Introduction.\u003c\/p\u003e \u003cp\u003e24.2 Molecular Structure Determination.\u003c\/p\u003e \u003cp\u003e24.3 Grid Computing in Buffalo.\u003c\/p\u003e \u003cp\u003e24.4 Center for Computational Research.\u003c\/p\u003e \u003cp\u003e24.5 ACDC-Grid Overview.\u003c\/p\u003e \u003cp\u003e24.6 Grid Research Collaborations.\u003c\/p\u003e \u003cp\u003e24.7 Grid Research Advancements.\u003c\/p\u003e \u003cp\u003e24.8 Grid Research Application Abstractions and Tools.\u003c\/p\u003e \u003cp\u003e24.9 Conclusions.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e25 GIPSY: A Problem-Solving Environment for Bioinformatics Applications\u003c\/b\u003e (\u003ci\u003eRajendra R. Joshi\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e25.1 Introduction.\u003c\/p\u003e \u003cp\u003e25.2 Architecture.\u003c\/p\u003e \u003cp\u003e25.3 Currently Deployed Applications.\u003c\/p\u003e \u003cp\u003e25.4 Conclusion.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e26 TaskSpaces: A Software Framework for Parallel Bioinformatics on Computational Grids\u003c\/b\u003e (\u003ci\u003eHans De Sterck\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e26.1 Introduction.\u003c\/p\u003e \u003cp\u003e26.2 The TaskSpaces Framework.\u003c\/p\u003e \u003cp\u003e26.3 Application: Finding Correctly Folded RNA Motifs.\u003c\/p\u003e \u003cp\u003e26.4 Case Study: Operating the Framework on a Computational Grid.\u003c\/p\u003e \u003cp\u003e26.5 Results for the RNA Motif Problem.\u003c\/p\u003e \u003cp\u003e26.6 FutureWork.\u003c\/p\u003e \u003cp\u003e26.7 Summary and Conclusion.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e27 The Organic Grid: Self-Organizing Computational Biology on Desktop Grids\u003c\/b\u003e (\u003ci\u003eArjav J. Chakravarti\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e27.1 Introduction.\u003c\/p\u003e \u003cp\u003e27.2 Background and RelatedWork.\u003c\/p\u003e \u003cp\u003e27.3 Measurements.\u003c\/p\u003e \u003cp\u003e27.4 Conclusions.\u003c\/p\u003e \u003cp\u003e27.5 Future Directions.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e28 FPGA Computing in Modern Bioinformatics\u003c\/b\u003e (\u003ci\u003eH. Simmler\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e28.1 Parallel Processing Models.\u003c\/p\u003e \u003cp\u003e28.2 Image Processing Task.\u003c\/p\u003e \u003cp\u003e28.3 FPGA Hardware Accelerators.\u003c\/p\u003e \u003cp\u003e28.4 Image Processing Example.\u003c\/p\u003e \u003cp\u003e28.5 Case Study: Protein Structure Prediction.\u003c\/p\u003e \u003cp\u003e28.6 Conclusion.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e29 Virtual Microscopy: Distributed Image Storage, Retrieval, Analysis, and Visualization\u003c\/b\u003e (\u003ci\u003eT. Pan\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e29.1 Introduction.\u003c\/p\u003e \u003cp\u003e29.2 Architecture.\u003c\/p\u003e \u003cp\u003e29.3 Image Analysis.\u003c\/p\u003e \u003cp\u003e29.4 Clinical Use.\u003c\/p\u003e \u003cp\u003e29.5 Education.\u003c\/p\u003e \u003cp\u003e29.6 Future Directions.\u003c\/p\u003e \u003cp\u003e29.7 Summary.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eIndex.\u003c\/b\u003e\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49402660454743,"sku":"9780471718482","price":159.26,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9780471718482.jpg?v=1730481148","url":"https:\/\/bookcurl.com\/products\/parallel-computing-for-bioinformatics-and-computational-biology-models-enabling-technologies-and-case-studies-55-wiley-series-on-parallel-and-distributed-computing-9780471718482","provider":"Book Curl","version":"1.0","type":"link"}