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. Ed(S): Carugo, Oliviero; Eisenhaber, Frank - Data Mining Techniques for the Life Sciences - 9781493935703 - V9781493935703
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Data Mining Techniques for the Life Sciences

€ 202.18
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Description for Data Mining Techniques for the Life Sciences Hardback. Editor(s): Carugo, Oliviero; Eisenhaber, Frank. Series: Methods in Molecular Biology. Num Pages: 552 pages, 13 black & white illustrations, 84 colour illustrations, 39 black & white tables, biograp. BIC Classification: PSA; UNF. Category: (P) Professional & Vocational. Dimension: 254 x 178 x 32. Weight in Grams: 1250.

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 ... Read more

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.


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Product Details

Format
Hardback
Publication date
2016
Publisher
Humana Press Inc. United States
Number of pages
552
Condition
New
Series
Methods in Molecular Biology
Number of Pages
552
Place of Publication
Totowa, NJ, United States
ISBN
9781493935703
SKU
V9781493935703
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15

Reviews for Data Mining Techniques for the Life Sciences
“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 ... Read more

Goodreads reviews for Data Mining Techniques for the Life Sciences


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