A01=Laxmi Parida
advanced statistical modelling
Author_Laxmi Parida
biological data mining
Boolean Expression
Category=PS
Category=UYQP
Compact Lists
Complete Binary Tree
computational genomics
Density Constraint
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eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
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Extensible Patterns
Homologous Sets
information theory applications
Input Graph
Input Sequences
Leaf Nodes
Location List
mathematical pattern recognition in bioinformatics
Maximal Motifs
Maximal Pattern
motif detection algorithms
Motif Profile
Nontrivial Interval
Partial Order
Permutation Pattern
Random Permutation
Random Trial
Rigid Pattern
sequence analysis techniques
Sequence Si
Solid Characters
String Patterns
Suffix Tree
Topological Motifs
V2 V3 V4
Product details
- ISBN 9781584885498
- Weight: 1140g
- Dimensions: 156 x 234mm
- Publication Date: 04 Jul 2007
- Publisher: Taylor & Francis Inc
- Publication City/Country: US
- Product Form: Hardback
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The computational methods of bioinformatics are being used more and more to process the large volume of current biological data. Promoting an understanding of the underlying biology that produces this data, Pattern Discovery in Bioinformatics: Theory and Algorithms provides the tools to study regularities in biological data.
Taking a systematic approach to pattern discovery, the book supplies sound mathematical definitions and efficient algorithms to explain vital information about biological data. It explores various data patterns, including strings, clusters, permutations, topology, partial orders, and boolean expressions. Each of these classes captures a different form of regularity in the data, providing possible answers to a wide range of questions. The book also reviews basic statistics, including probability, information theory, and the central limit theorem.
This self-contained book provides a solid foundation in computational methods, enabling the solution of difficult biological questions.
Parida, Laxmi
