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008			220504s2022 xxua o |||| 0|eng d
020			_a9781071620953
024	7		_a10.1007/978-1-0716-2095-3 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQH324.2 _b2022 EB
245	0	0	_aData Mining Techniques for the Life Sciences _cedited by Oliviero Carugo, Frank Eisenhaber
250			_a3rd edition 2022
264		1	_aNew York, NY _bSpringer International Publising _c2022
300			_a1 recurso en línea (XIII, 390 páginas) _b88 ilustraciones, 77 ilustraciones a color
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aMethods in Molecular Biology _x1940-6029 _v2449
505	0		_a EBI data resources -- IMEx databases: displaying molecular interactions into a single, standards-compliant dataset -- Protein Three-dimensional Structure Databases -- Predicting protein conformational disorder and disordered binding sites -- Profiles of natural and designed protein-like sequences effectively bridge protein sequence gaps: Implications in distant homology detection -- Turning failures into applications: the problem of protein ΔΔG prediction -- Dissecting the genome for drug response prediction -- Prediction of the effect of pH on the aggregation and conditional folding of intrinsically disordered proteins with SolupHred and DispHred -- Extracting the dynamic motion of proteins using Normal Mode Analysis -- Pre- and Post- Publication Verification for Reproducible Data Mining in Macromolecular Crystallography -- Soft Statistical Mechanics for Biology -- Uses and abuses of the atomic displacement parameters in structural biology -- Optimizing the Parametrization of Homologue Classification in the Pan-Genome Computation for a Bacterial Species: Case Study Streptococcus pyogenes -- Computational pipeline for rational drug combination screening in patient-derived cells -- Deep Mining from Omics Data.
520			_aThis 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 further their study in this field.
988			_aSpringer_Protocols_2022
650		7	_2embne _9160489 _aBioinformática
650		7	_2embne _9162648 _aData mining
776	0	8	_iPrinted edition: _z9781071620946
776	0	8	_iPrinted edition: _z9781071620960
776	0	8	_iPrinted edition: _z9781071620977
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-1-0716-2095-3 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b07/2023 _dz _eb _zSI