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Data Mining Techniques for the Life Sciences - Methods in Molecular Biology 1415 (Paperback)
  • Data Mining Techniques for the Life Sciences - Methods in Molecular Biology 1415 (Paperback)
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Data Mining Techniques for the Life Sciences - Methods in Molecular Biology 1415 (Paperback)

(editor), (editor)
£109.99
Paperback 552 Pages / Published: 21/04/2018
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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.


Publisher: Humana Press Inc.
ISBN: 9781493980819
Number of pages: 552
Weight: 1068 g
Dimensions: 254 x 178 x 29 mm
Edition: Softcover reprint of the original 2nd ed. 201


MEDIA REVIEWS
"The style of the book and the assortment of topics which are presented make it accessible to a wide range of audiences, from undergraduates to established researchers, and from a variety of backgrounds, biologists, chemists, bioinformaticians. This collection of articles highlighting the state of the art for protein analyses, can also be used as a brief yet thorough starting point for post-graduate projects." (Irina Ioana Mohorianu, zbMATH 1353.92002, 2017)

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