| Description |
1 online resource (xx, 332 pages) : illustrations (some color) |
| Series |
Science, engineering, and biology informatics ; v. 3 |
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Science, engineering, and biology informatics ; v. 3
|
| Contents |
pt. I. Overview. ch. 1. Bioinformatics: mining the massive data from high throughput genomics experiments / Haixu Tang and Sun Kim. ch. 2. An introduction to soft computing / Amit Konar and Swagatam Das -- pt. II. Biological sequence and structure analysis. ch. 3. Reconstructing phylogenies with memetic algorithms and branch-and-bound / José E. Gallardo, Carlos Cotta and Antonio J. Fernández. ch. 4. Classification of RNA sequences with support vector machines / Jason T.L. Wang and Xiaoming Wu. ch. 5. Beyond string algorithms: protein sequence analysis using wavelet transforms / Arun Krishnan and Kuo-Bin Li. ch. 6. Filtering protein surface motifs using negative instances of active sites candidates / Nripendra L. Shrestha and Takenao Ohkawa. ch. 7. Distill: a machine learning approach to Ab Initio protein structure prediction / Gianluca Pollastri, Davide Baú and Alessandro Vullo. ch. 8. In silico design of ligands using properties of target active sites / Sanghamitra Bandyopadhyay [and others] -- pt. III. Gene expression and microarray data analysis. ch. 9. Inferring regulations in a genomic network from gene expression profiles. ch. 10. A reliable classification of gene clusters for cancer samples using a hybrid multi-objective evolutionary procedure / Kalyanmoy Deb, A. Raji Reddy and Shamik Chaudhuri. ch. 11. Feature selection for cancer classification using ant colony optimization and support vector machines / A. Gupta, V.K. Jayaraman and B.D. Kulkarni. ch. 12. Sophisticated methods for cancer classification using microarray data / Sung-Bae Cho and Han-Saem Park. ch. 13. Multiobjective evolutionary approach to fuzzy clustering of microarray data / Anirban Mukhopadhyay, Ujjwal Maulik and Sanghamitra Bandyopadhyay |
| Summary |
Bioinformatics, a field devoted to the interpretation and analysis of biological data using computational techniques, has evolved tremendously in recent years due to the explosive growth of biological information generated by the scientific community. Soft computing is a consortium of methodologies that work synergistically and provides, in one form or another, flexible information processing capabilities for handling real-life ambiguous situations. Several research articles dealing with the application of soft computing tools to bioinformatics have been published in the recent past; however, |
| Bibliography |
Includes bibliographical references and index |
| Notes |
Online resource; title from PDF title page (ProQuest Ebook Central, viewed March 17, 2021) |
| Subject |
Bioinformatics.
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Soft computing.
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Computational biology.
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Artificial intelligence.
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Computational Biology
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Artificial Intelligence
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artificial intelligence.
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COMPUTERS -- Bioinformatics.
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Bioinformatics
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Soft computing
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| Genre/Form |
Methods (Music)
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| Form |
Electronic book
|
| Author |
Bandyopadhyay, Sanghamitra, 1968- editor
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Maulik, Ujjwal, editor
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Wang, Jason T. L., editor
|
| ISBN |
9789812708892 |
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9812708898 |
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