Provides systematic treatment of the application of data mining in bioinformatics, in a manner that is accessible to a computer-literate reader who understands the basics of genetics as well as to computationally interested biologists. Of particular interest to researchers in data mining and bioinformatics. The book is aimed at computer scientists, so necessary biology is explained as needed. Finally, problems are provided at the end of several chapters in case readers want to use the book as a text.

No known book on this area First book containing the work of key researchers in biological data mining Presents new techniques on (a) gene expression data mining, (b) gene mapping for disease detection, and (c) phylogenetic knowledge discovery, which are of increasing importance but are absent in all previously published books in the area of computational biology Organized around the major themes of modern biology: sequence studies, proteomics and developmental biology - these are core areas of present and future research Includes supplementary material: sn.pub/extras

Klappentext

Written especially for computer scientists, all necessary biology is explained.

Presents new techniques on gene expression data mining, gene mapping for disease detection, and phylogenetic knowledge discovery.

Inhalt
Overview.- to Data Mining in Bioinformatics.- Survey of Biodata Analysis from a Data Mining Perspective.- Sequence and Structure Alignment.- AntiClustAl: Multiple Sequence Alignment by Antipole Clustering.- RNA Structure Comparison and Alignment.- Biological Data Mining.- Piecewise Constant Modeling of Sequential Data Using Reversible Jump Markov Chain Monte Carlo.- Gene Mapping by Pattern Discovery.- Predicting Protein Folding Pathways.- Data Mining Methods for a Systematics of Protein Subcellular Location.- Mining Chemical Compounds.- Biological Data Management.- Phyloinformatics: Toward a Phylogenetic Database.- Declarative and Efficient Querying on Protein Secondary Structures.- Scalable Index Structures for Biological Data.