{"product_id":"data-mining-techniques-for-the-life-sciences-9781071620946","title":"Data Mining Techniques for the Life Sciences","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eThis third edition details new and updated methods and protocols on important databases and data mining tools. Chapters guides readers through archives of macromolecular sequences and three-dimensional structures, databases of protein-protein interactions, methods for prediction conformational disorder, mutant thermodynamic stability, aggregation, and drug response. Quality of structural data and their release, soft mechanics applications in biology, and protein flexibility are considered, too, together with pan-genome analyses, rational drug combination screening and Omics Deep Mining. Written in the format of the highly successful Methods in Molecular Biology series, each chapter includes an introduction to the topic, lists necessary materials, includes step-by-step, readily reproducible protocols.   Authoritative and cutting-edge, Data Mining Techniques for the Life Sciences, Third Edition aims to be a practical guide to researches to help furthertheir study in this field.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e\u003cb\u003ePart I: DATABASES\u003c\/b\u003e\u003c\/p\u003e  \u003cp\u003e \u003c\/p\u003e  \u003cp\u003e1 EBI data resources\u003c\/p\u003e  \u003cp\u003eRolf Apweiler and Amonida Zadissa\u003c\/p\u003e  \u003cp\u003e \u003c\/p\u003e  \u003cp\u003e2 IMEx databases: displaying molecular interactions into a single, standards-compliant dataset\u003c\/p\u003e  \u003cp\u003ePablo Porras, Sandra Orchard and Luana Licata\u003c\/p\u003e  \u003cp\u003e \u003c\/p\u003e  \u003cp\u003e3 Protein Three-dimensional Structure Databases\u003c\/p\u003e  \u003cp\u003eVaishali P. Waman, Christine Orengo, Gerard J. Kleywegt and Arthur M. Lesk\u003c\/p\u003e  \u003cp\u003e \u003c\/p\u003e  \u003cp\u003e\u003cb\u003ePart II:  PREDICTION METHODS\u003c\/b\u003e\u003c\/p\u003e  \u003cp\u003e \u003c\/p\u003e  \u003cp\u003e4 Predicting protein conformational disorder and disordered binding sites\u003c\/p\u003e  \u003cp\u003eKetty Tamburrini, Giulia Pesce, Juliet Nilsson, Frank Gondelaud, Andrey V. Kajava, Jean-Guy Berrin and Sonia Longhi\u003c\/p\u003e  \u003cp\u003e \u003c\/p\u003e  \u003cp\u003e5 Profiles of natural and designed protein-like sequences effectively bridge protein sequence gaps: Implications in distant homology detection\u003c\/p\u003e  \u003cp\u003eGayatri Kumar, Narayanaswamy Srinivasa and Sankaran Sandhya \u003c\/p\u003e   \u003cp\u003e \u003c\/p\u003e  \u003cp\u003e6 Turning failures into applications: the problem of protein ΔΔG prediction\u003c\/p\u003e  \u003cp\u003eRita Casadio, Castrense Savojardo, Piero Fariselli, Emidio Capriotti and Pier Luigi Martelli\u003c\/p\u003e  \u003cp\u003e \u003c\/p\u003e  \u003cp\u003e7 Dissecting the genome for drug response prediction\u003c\/p\u003e  \u003cp\u003eGerardo Pepe, Chiara Carrino, Luca Parca, Manuela Helmer-Citterich\u003c\/p\u003e  \u003cp\u003e \u003c\/p\u003e  \u003cp\u003e8 Prediction of the effect of pH on the aggregation and conditional folding of intrinsically disordered proteins with SolupHred and DispHred\u003c\/p\u003e  \u003cp\u003eValentín Iglesias, Carlos Pintado-Grima, Jaime Santos, Marc Fornt and Salvador Ventura\u003c\/p\u003e  \u003cp\u003e \u003c\/p\u003e  \u003cp\u003e9 Extracting the dynamic motion of proteins using Normal Mode Analysis\u003c\/p\u003e  \u003cp\u003eJacob A. Bauer and Vladena Bauerová\u003c\/p\u003e   \u003cp\u003e \u003c\/p\u003e  \u003cp\u003e\u003cb\u003ePart III: DATA QUALITY\u003c\/b\u003e\u003c\/p\u003e  \u003cp\u003e \u003c\/p\u003e  \u003cp\u003e10 Pre- and Post- Publication Verification for Reproducible Data Mining in Macromolecular Crystallography\u003c\/p\u003e  \u003cp\u003eJohn R Helliwell\u003c\/p\u003e  \u003cp\u003e \u003c\/p\u003e  \u003cp\u003e11 Soft Statistical Mechanics for Biology\u003c\/p\u003e  \u003cp\u003eMariano Bizzarri, Alessandro Giuliani\u003c\/p\u003e  \u003cp\u003e \u003c\/p\u003e  \u003cp\u003e12 Uses and abuses of the atomic displacement parameters in structural biology\u003c\/p\u003e  Oliviero Carugo  \u003cp\u003e \u003c\/p\u003e  \u003cp\u003e13 Optimizing the Parametrization of Homologue Classification in the Pan-Genome Computation for a Bacterial Species: Case Study Streptococcus pyogenes\u003c\/p\u003e   \u003cp\u003eErwin Tantoso, Birgit Eisenhaber and Frank Eisenhaber\u003c\/p\u003e  \u003cp\u003e \u003c\/p\u003e  \u003cp\u003e\u003cb\u003ePart VI: BIG DATA\u003c\/b\u003e\u003c\/p\u003e  \u003cp\u003e \u003c\/p\u003e  \u003cp\u003e14 Computational pipeline for rational drug combination screening in patient-derived cells\u003c\/p\u003e  \u003cp\u003ePaschalis Athanasiadis, Aleksandr Ianevski, Sigrid Skånland and Tero Aittokallio\u003c\/p\u003e  \u003cp\u003e \u003c\/p\u003e  \u003cp\u003e15 Deep Mining from Omics Data\u003c\/p\u003e  \u003cp\u003eAbeer Alzubaidi and Jonathan Tepper\u003c\/p\u003e","brand":"Springer-Verlag New York Inc.","offers":[{"title":"Default Title","offer_id":53186413560151,"sku":"9781071620946","price":151.99,"currency_code":"GBP","in_stock":true}],"url":"https:\/\/bookcurl.com\/products\/data-mining-techniques-for-the-life-sciences-9781071620946","provider":"Book Curl","version":"1.0","type":"link"}