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Data mining in bioinformatics / Jason T.L. Wang ... [et al.].

Contributor(s): Material type: TextTextPublication details: New Delhi : Springer, 2005.Description: xi, 340 p. : ill. ; 21 cmISBN:
  • 9788181285323
  • 8181285328
Subject(s): DDC classification:
  • 572.802856312   22
Contents:
Overview An Introduction to Data Mining in Bioinformatics A Survey of Bio-Data Analysis from Data Mining Perspective -- Sequence and Structure Alignment ANTICLUSTRAL: Multiple Sequence Alignment by Antipole Clustering RNA Structyre Comparison and Alignment Part -- Biological Data Mining Piecewise Constant Modeling of Sequential Data using Reversible Jump Markov Chain Monte Carlo Gene Mapping by Pattern Discovery Prediciting Protein Folding Pathways Data Mining Methods for a Systematics of Protein Subcellular Location Mining Chemical Compounds -- Biological Data Managment Phyloinformatics: Towards a Phylogenetic Database Declarative and Efficinet Querying on Protein Secondary Sturctures Scalable Index Structures for Biological Data Glossary References Biographies Index.
Summary: The goal of this book is to help readers understand state-of-the-art techniques in biological data mining and data management and includes topics such as: - preprocessing tasks such as data cleaning and data integration as applied to biological data - classification and clustering techniques for microarrays - comparison of RNA structures based on string properties and energetics - discovery of the sequence characteristics of different parts of the genome - mining of haplotypes to find disease markers - sequencing of events leading to the folding of a protein - inference of the subcellular location of protein activity - classification of chemical compounds based on structure - special purpose metrics and index structures for phylogenetic applications - a new query language for protein searching based on the shape of proteins - very fast indexing schemes for sequences and pathways Aimed at computer scientists, necessary biology is explained.
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Books Books Main library General Stacks 572.802856312 / WA.D (Browse shelf(Opens below)) 1 Available 006146

Includes bibliographical references (p. [303]-326) and index.

Overview An Introduction to Data Mining in Bioinformatics A Survey of Bio-Data Analysis from Data Mining Perspective -- Sequence and Structure Alignment ANTICLUSTRAL: Multiple Sequence Alignment by Antipole Clustering RNA Structyre Comparison and Alignment Part -- Biological Data Mining Piecewise Constant Modeling of Sequential Data using Reversible Jump Markov Chain Monte Carlo Gene Mapping by Pattern Discovery Prediciting Protein Folding Pathways Data Mining Methods for a Systematics of Protein Subcellular Location Mining Chemical Compounds -- Biological Data Managment Phyloinformatics: Towards a Phylogenetic Database Declarative and Efficinet Querying on Protein Secondary Sturctures Scalable Index Structures for Biological Data Glossary References Biographies Index.

The goal of this book is to help readers understand state-of-the-art techniques in biological data mining and data management and includes topics such as: - preprocessing tasks such as data cleaning and data integration as applied to biological data - classification and clustering techniques for microarrays - comparison of RNA structures based on string properties and energetics - discovery of the sequence characteristics of different parts of the genome - mining of haplotypes to find disease markers - sequencing of events leading to the folding of a protein - inference of the subcellular location of protein activity - classification of chemical compounds based on structure - special purpose metrics and index structures for phylogenetic applications - a new query language for protein searching based on the shape of proteins - very fast indexing schemes for sequences and pathways Aimed at computer scientists, necessary biology is explained.

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