Grid Computing For Bioinformatics And Computational Biology

The only single, up-to-date source for Grid issues in bioinformatics and biology Bioinformatics is fast emerging as an important discipline for academic research and industrial applications, creating a need for the use of Grid computing techniques for large-scale distributed applications. The only single, up-to-date source for Grid issues in bioinformatics and biology Bioinformatics is fast emerging as an important discipline for academic research and industrial applications, creating a need for the use of Grid computing techniques for large-scale distributed applications. This book successfully presents Grid algorithms and their real-world applications, provides details on modern and ongoing research, and explores software frameworks that integrate bioinformatics and computational biology. Additional coverage includes: Bio-ontology and data mining Data visualization DNA assembly, clustering, and mapping Molecular evolution and phylogeny Gene expression and micro-arrays Molecular modeling and simulation Sequence search and alignment Protein structure prediction Grid infrastructure, middleware, and tools for bio data Grid Computing for Bioinformatics and Computational Biology is an indispensable resource for professionals in several research and development communities including bioinformatics, computational biology, Grid computing, data mining, and more. It also serves as an ideal textbook for undergraduate- and graduate-level courses in bioinformatics and Grid computing. The only single, up-to-date source for Grid issues in bioinformatics and biology Bioinformatics is fast emerging as an important discipline for academic research and industrial applications, creating a need for the use of Grid computing techniques for large-scale distributed applications. This book successfully presents Grid algorithms and their real-world applications, provides details on modern and ongoing research, and explores software frameworks that integrate bioinformatics and computational biology. Additional coverage includes: * Bio-ontology and data mining * Data visualization * DNA assembly, clustering, and mapping * Molecular evolution and phylogeny * Gene expression and micro-arrays * Molecular modeling and simulation * Sequence search and alignment * Protein structure prediction * Grid infrastructure, middleware, and tools for bio data Grid Computing for Bioinformatics and Computational Biology is an indispensable resource for professionals in several research and development communities including bioinformatics, computational biology, Grid computing, data mining, and more. It also serves as an ideal textbook for undergraduate- and graduate-level courses in bioinformatics and Grid computing.