Parallel Computing for Bioinformatics and Computational Biology : Models, Enabling Technologies, and Case Studies

Albert Y Zomaya

ISBN 10: 0471718483 / ISBN 13: 9780471718482

Published by Wiley Apr 2006, 2006

About this Item

Neuware - Discover how to streamline complex bioinformatics applications with parallel computingThis 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 technologiesResearchers, 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.

Seller Inventory # 9780471718482

Bibliographic Details

• Title: Parallel Computing for Bioinformatics and Computational Biology : Models, Enabling Technologies, and Case Studies
• Publisher: Wiley Apr 2006
• Publication Date: 2006
• Language: English
• ISBN 10: 0471718483
• ISBN 13: 9780471718482
• Binding: Buch
• Condition: Neu
• Dimensions: 244W x 164H x 42D millimeters 244 millimeters width by 164 millimeters height by 42 millimeters depth
• Weight: 1286 grams

About this title

Synopsis

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.

About the Author

ALBERT Y. ZOMAYA is the CISCO Systems Chair Professor of Internetworking, School of Information Technologies, The University of Sydney, and Deputy Director for Information Technology of the Sydney University Biological Informatics and Technology Centre. Professor Zomaya has been the Chair of the IEEE Technical Committee on Parallel Processing and has been awarded the IEEE Computer Society's Meritorious Service Award. He is an IEEE fellow.