{"product_id":"parallel-computing-for-bioinformatics-and-computational-biology-models-enabling-technologies-and-case-studies-hardback-9780471718482","title":"Parallel Computing for Bioinformatics and Computational Biology; Models, Enabling Technologies, and Case Studies (Hardback) 9780471718482","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eParallel Computing for Bioinformatics and Computational Biology\u003c\/font\u003e\u003cbr\u003e\r\n\u003cfont size=\"5\"\u003eModels, Enabling Technologies, and Case Studies\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\u003cp\u003e\u003cfont size=\"4\"\u003eAlbert Y. Zomaya (Edited by), AY Zomaya (Author)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9780471718482, Wiley\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 23 May 2006\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e816 pages, Drawings: 150 B\u0026amp;W, 0 Color\u003cbr\u003e24.2 x 16 x 4.2 cm, 1.282 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cem\u003e\u003cfont size=\"3\"\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\u003c\/font\u003e\u003c\/em\u003e\u003c\/p\u003e\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003eDiscover how to streamline complex bioinformatics applications with parallel computing\u003cbr\u003e \u003cbr\u003e \u003cbr\u003e This publication enables readers to handle more complex bioinformatics applications and larger and richer data sets. As the editor clearly shows, using powerful parallel computing tools can lead to significant breakthroughs in deciphering genomes, understanding genetic disease, designing customized drug therapies, and understanding evolution.\u003cbr\u003e \u003cbr\u003e A broad range of bioinformatics applications is covered with demonstrations on how each one can be parallelized to improve performance and gain faster rates of computation. Current parallel computing techniques and technologies are examined, including distributed computing and grid computing. Readers are provided with a mixture of algorithms, experiments, and simulations that provide not only qualitative but also quantitative insights into the dynamic field of bioinformatics.\u003cbr\u003e \u003cbr\u003e Parallel Computing for Bioinformatics and Computational Biology is a contributed work that serves as a repository of case studies, collectively demonstrating how parallel computing streamlines difficult problems in bioinformatics and produces better results. Each of the chapters is authored by an established expert in the field and carefully edited to ensure a consistent approach and high standard throughout the publication.\u003cbr\u003e \u003cbr\u003e The work is organized into five parts:\u003cbr\u003e * Algorithms and models\u003cbr\u003e * Sequence analysis and microarrays\u003cbr\u003e * Phylogenetics\u003cbr\u003e * Protein folding\u003cbr\u003e * Platforms and enabling technologies\u003cbr\u003e \u003cbr\u003e Researchers, educators, and students in the field of bioinformatics will discover how high-performance computing can enable them to handle more complex data sets, gain deeper insights, and make new discoveries.\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\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\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Computer science [\u003ca title=\"See our other books on Computer science\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Computer%20science%20%5BUY%5D%22\"\u003eUY\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Wiley-Interscience","offers":[{"title":"Brand New","offer_id":52298042605848,"sku":"9780471718482","price":139.99,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9780471718482.jpg?v=1781732208","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/parallel-computing-for-bioinformatics-and-computational-biology-models-enabling-technologies-and-case-studies-hardback-9780471718482","provider":"Freshly Printed Books","version":"1.0","type":"link"}