Grid Computing for Bioinformatics and Computational Biology
(Sprache: Englisch)
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...
Bioinformatics is fast emerging as an important discipline for academic research and industrial applications, creating a need for the use of Grid computing techniques...
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Klappentext zu „Grid Computing for Bioinformatics and Computational Biology “
The only single, up-to-date source for Grid issues in bioinformatics and biologyBioinformatics 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:
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Bio-ontology and data mining
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Data visualization
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DNA assembly, clustering, and mapping
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Molecular evolution and phylogeny
*
Gene expression and micro-arrays
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Molecular modeling and simulation
*
Sequence search and alignment
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Protein structure prediction
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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.
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.
Inhaltsverzeichnis zu „Grid Computing for Bioinformatics and Computational Biology “
- Preface- Chapter 1: Open computing Grid for molecular sciences (M. Romberg, E. Benfenati, and W. Dubitzky)
- Chapter 2: Designing high-performance concurrent strategies for biological sequence alignment problems on networked computing platforms (B. Veeravalli)
- Chapter 3: Optimized cluster-enabled HMMER searches (J. P. Walters, J. Landman, and V. Chaudhary)
- Chapter 4: Expanding the rich of Grid computing: combining Globus and BOINC based systems (D. S. Myers, A. L. Bazinet, and M. P. Cummings)
- Chapter 5: Hierarchical Grid computing for high performance bioinformatics (B. Schmidt, C.X. Chen and W. Liu)
- Chapter 6:Multiple sequence alignment and phylogenetic inference (D. Trystram, and J. Zola)
- Chapter 7: Data syndication techniques for bioinformatics applications (C. Wang, A. Y. Zomaya, and B. B. Zhou)
- Chapter 8: Conformational sampling and docking on Grids (A. Tantar, N. Melab, and E-G. Talbi)
- Chapter 9: Deployment of Grid life sciences applications (V. Breton, N. Jacq, V. Kasam, and J. Salzemann)
- Chapter 10: Grid-based interactive decision support in biomedicine (A. Tirado-Ramos, P. M. A. Sloot, and M. Bubak)
- Chapter 11: Database-driven grid computing and distributed web applications: a comparison (H. De Sterck, A.Papo, C. Zhang, M. Hamady, and R. Knight)
- Chapter 12: A semantic mediation architecture for a clinical Data Grid (K. Kumpf, A. Wohrer, S. Benkner, G. Engelbrecht, and Jochen Fingberg)
- Chapter 13: Bioinformatics applications in Grid computing environments (A. Boukerche, A. C. Magalhaes and Alves De Melo)
- Chapter 14: Recent advances in solving the protein threading problem (R. Andonov, G. Collet, J-F. Gibrat, A. Marin, V. Poirriez, and N. Yanev)
- Chapter 15: DNA fragment assembly using Grid systems (A. J. Nebro, G. Luque, and E. Alba)
- Chapter 16: Seeing is knowing: Visualization of parameter-parameter dependencies in biomedical network models (A. Konagaya, R. Azuma, R. Umetsu, S.
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Ohki, F. Konishi, K. Matsumura, and S. Yoshikawa).
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Autoren-Porträt von Talbi, Zomaya
El-Ghazali Talbi, PhD, is a Full Professor in the Computer Science Laboratory at the Université de Lille, Centre National de la Recherche Scientifique, and Institut National de Recherche en Informatique et en Automatique in France. Dr. Talbi has contributed to numerous publications in international journals and conferences and has organized many workshops and sessions discussing parallel and distributed computing for bioinformatics.Albert Y. Zomaya, PhD, is the CISCO Systems Chair Professor of Internet-working in the School of Information Technologies at the University of Sydney. He also serves as Deputy Director for the Sydney University Biological Informatics and Technology Center and is the author or coauthor of several books and publications.
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