Data Mining in Bioinformatics (Hardcover)

Jason T.L. Wang

ISBN 10: 1852336714 / ISBN 13: 9781852336714

Editore: Springer London Ltd, England, 2004

Riguardo questo articolo

Hardcover. 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. Protein subcellular location is important for understanding protein function inside the cell. The context of protein functionality is well represented by protein subcellular location. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Codice articolo 9781852336714

Dati bibliografici

• Titolo: Data Mining in Bioinformatics (Hardcover)
• Editore: Springer London Ltd, England
• Data di pubblicazione: 2004
• Lingua: Inglese
• ISBN 10: 1852336714
• ISBN 13: 9781852336714
• Rilegatura: Hardcover
• Condizione: new

Descrizione articolo

Riassunto

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.

Contenuti

Part I - Overview An Introduction to Data Mining in Bioinformatics A Survey of Bio-Data Analysis from Data Mining Perspective Part II - Sequence and Structure Alignment ANTICLUSTRAL: Multiple Sequence Alignment by Antipole Clustering RNA Structyre Comparison and Alignment Part III - 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 Part IV - 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