Data Mining Techniques for the Life Sciences [Hardcover]

This volume details several important databases and data mining tools. Data Mining Techniques for the Life Sciences, Second Edition guides readers through archives of macromolecular three-dimensional structures, databases of protein-protein interactions, thermodynamics information on protein and mutant stability, Kbdock protein domain structure database, PDB_REDO databank, erroneous sequences, substitution matrices, tools to align RNA sequences, interesting procedures for kinase family/subfamily classifications, new tools to predict protein crystallizability, metabolomics data, drug-target interaction predictions, and a recipe for protein-sequence-based function prediction and its implementation in the latest version of the ANNOTATOR software suite. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls.

Authoritative and cutting-edge, Data Mining Techniques for the Life Sciences, Second Edition aims to ensure successful results in the further study of this vital field.

Part I: Data Basses

1. Update on Genomic Databases and Resources at the National Center for Biotechnology Information

Tatiana Tatusova

2. Protein Structure Databases

Roman A. Laskowski

3. The MIntAct Project and Molecular Interaction Databases

Luana Licata and Sandra Orchard

4. Applications of Protein Thermodynamic Database for Understanding Protein Mutant Stability and Designing Stable Mutants

M. Michael Gromiha, P. Anoosha, and Liang-Tsung Huang