Sequence Data MiningSpringer Science & Business Media, 2007年10月31日 - 150 頁 This book provides balanced coverage of the existing results on sequence data mining as well as pattern types and associated pattern mining methods. While there are several books on data mining and sequence data analysis, currently there are no books that balance both of these topics. This volume fills in the gap, allowing readers to access the state-of-the-art results in one place. Sequence Data Mining is designed for professionals working in bioinformatics, genomics, web services, and financial data analysis. This book is also suitable for advanced-level students in computer science and bioengineering. |
內容
Introduction | 1 |
Frequent and Closed Sequence Patterns | 14 |
Classification Clustering Features and Distances of Sequence Data | 47 |
Identifying and Characterizing Sequence Families | 67 |
Mining Partial Orders from Sequences | 88 |
Distinguishing Sequence Patterns | 113 |
Related Topics | 131 |
| 139 | |
| 147 | |
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常見字詞
alignment alphabet amino acids anti-monotonic applications bioinformatics biological sequence bitset array breadth-first search candidate sequences closed partial orders closed sequential patterns complete set compute considered dataset defined depth-first search discussed distance functions distinguishing sequence patterns DNA sequences element example Figure Frecpo frequent closed partial frequent partial orders gene Gibbs sampling given sequence global hidden Markov models identify itemsets Markov chain Markov models mask bitset match matrix maximum gap constraint min_sup minimization mining frequent mining process monotonic node nxt(q occurrence partial periodic patterns pattern-growth patterns with prefix Prefix-growth prefix-monotone PrefixSpan projected database protein sequence pruning Pseudocounts quences recursively regular expression regular expression constraint satisfying the constraint scan sequence clustering sequence data mining sequence database sequence families sequential pattern mining set of items set of sequential similarity subsequence subset suffix total order transaction transitive closure transitive reduction types URLs
熱門章節
第 139 頁 - A. Bateman, E. Birney, L. Cerruti, R. Durbin, L. Etwiller, SR Eddy, S. GriffithsJones, KL Howe, M. Marshall, and ELL Sonnhammer. The Pfam protein families database.