Parallel Computing for Bioinformatics and Computational Biology

Discover how to streamline complex bioinformatics applications with parallel computing 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. 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. 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. The work is organized into five parts: * Algorithms and models * Sequence analysis and microarrays * Phylogenetics * Protein folding * Platforms and enabling technologies 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.

Discover how to streamline complex bioinformatics applications withparallel computingThis publication enables readers to handle more complexbioinformatics applications and larger and richer data sets. As theeditor clearly shows, using powerful parallel computing tools canlead to significant breakthroughs in deciphering genomesunderstanding genetic disease, designing customized drug therapiesand understanding evolution.A broad range of bioinformatics applications is covered withdemonstrations on how each one can be parallelized to improveperformance and gain faster rates of computation. Current parallelcomputing techniques and technologies are examined, includingdistributed computing and grid computing. Readers are provided witha mixture of algorithms, experiments, and simulations that providenot only qualitative but also quantitative insights into thedynamic field of bioinformatics.Parallel Computing for Bioinformatics and Computational Biology isa contributed work that serves as a repository of case studiescollectively demonstrating how parallel computing streamlinesdifficult problems in bioinformatics and produces better results.Each of the chapters is authored by an established expert in thefield and carefully edited to ensure a consistent approach and highstandard throughout the publication.The work is organized into five parts:* Algorithms and models* Sequence analysis and microarrays* Phylogenetics* Protein folding* Platforms and enabling technologiesResearchers, educators, and students in the field of bioinformaticswill discover how high-performance computing can enable them tohandle more complex data sets, gain deeper insights, and make newdiscoveries.