- Full Description
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.
- Table of Contents
Table of Contents
- An Introduction to Data Mining in Bioinformatics.
- A Survey of Bio
- Data Analysis from Data Mining Perspective.
- ANTICLUSTRAL: Multiple Sequence Alignment by Antipole Clustering.
- RNA Structyre Comparison and Alignment.
- 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.
- Phyloinformatics: Towards a Phylogenetic Database.
- Declarative and Efficinet Querying on Protein Secondary Sturctures.
- Scalable Index Structures for Biological Data.
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