Pattern discovery in bioinformatics : Theory & algorithms
As in most scientific endeavors, bioinformatics requires more than a manual and a few anecdotes. Parida (no affiliation given) proves that researchers in bioinformatics need algorithmic and statistical expertise and ingenuity. Without using models she explains how to locate modes of regularities in...
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| 格式: | 圖書 |
| 語言: | Undetermined |
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Boca Raton
Chapman & Hall/CRC
2008
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| Thư viện lưu trữ: | Trung tâm Học liệu Trường Đại học Cần Thơ |
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| 020 | |c 1300000 | ||
| 082 | |a 572.80285 | ||
| 082 | |b P231 | ||
| 100 | |a Parida, Laxmi | ||
| 245 | 0 | |a Pattern discovery in bioinformatics : | |
| 245 | 0 | |b Theory & algorithms | |
| 245 | 0 | |c Laxmi Parida | |
| 260 | |a Boca Raton | ||
| 260 | |b Chapman & Hall/CRC | ||
| 260 | |c 2008 | ||
| 520 | |a As in most scientific endeavors, bioinformatics requires more than a manual and a few anecdotes. Parida (no affiliation given) proves that researchers in bioinformatics need algorithmic and statistical expertise and ingenuity. Without using models she explains how to locate modes of regularities in large amounts of biological data, including string patterns, patterned clusters, permutation patterns, topological patterns, partial order patterns, and boolean expressions. She starts with the fundamentals for novices, including basic algorithms and statistics and the characteristics of patterns, then moves on the biopolymers, Bernoulli schemes and Markov, string pattern specifications, algorithms and pattern statistics, motif learning and patterns on meta-data such as permutation patterns and their probabilities, topological motifs, set-theoretic algorithmic tools, expression and partial order motifs. | ||
| 650 | |a Bioinformatics,Pattern recognition systems,Computational biology,Tin học ứng dụng sinh học | ||
| 650 | |x Methods | ||
| 904 | |i Trọng Hải | ||
| 980 | |a Trung tâm Học liệu Trường Đại học Cần Thơ | ||