Computational text analysis for functional genomics and bioinformatics /
This book brings together the two disparate worlds of computational text analysis and biology and presents some of the latest methods and applications to proteomics, sequence analysis and gene expression data. Modern genomics generates large and comprehensive data sets but their interpretation requi...
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| Main Author: | |
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| Format: | Electronic eBook |
| Language: | English |
| Published: |
Oxford :
Oxford University Press,
2006.
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| Subjects: | |
| Online Access: | CONNECT |
MARC
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| 100 | 1 | |a Raychaudhuri, Soumya. | |
| 245 | 1 | 0 | |a Computational text analysis for functional genomics and bioinformatics / |c Soumya Raychaudhuri. |
| 260 | |a Oxford : |b Oxford University Press, |c 2006. | ||
| 300 | |a 1 online resource (xix, 288 pages) | ||
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| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a List of Figures; List of Plates; List of Tables; 1 An introduction to text analysis in genomics; 2 Functional genomics; 3 Textual profiles of genes; 4 Using text in sequence analysis; 5 Text-based analysis of a single series of gene expression measurements; 6 Analyzing groups of genes; 7 Analyzing large gene expression data sets; 8 Using text classfication for gene function annotation; 9 Finding gene names; 10 Protein interaction networks; 11 Conclusion; Index. | |
| 520 | |a This book brings together the two disparate worlds of computational text analysis and biology and presents some of the latest methods and applications to proteomics, sequence analysis and gene expression data. Modern genomics generates large and comprehensive data sets but their interpretation requires an understanding of a vast number of genes, their complex functions, and interactions. Keeping up with the literature on a single gene is a challenge itself-for thousands of genes it is simply. impossible. Here, Soumya Raychaudhuri presents the techniques and algorithms needed to access and util. | ||
| 588 | 0 | |a Print version record. | |
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| 650 | 0 | |a Genomics |x Data processing. | |
| 650 | 0 | |a Bioinformatics. | |
| 650 | 0 | |a Computational biology. | |
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