Data Mining Techniques for the Life Sciences
Springer-Verlag New York Inc.
978-1-0716-2097-7 (ISBN)
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.
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.
Erscheinungsdatum | 10.05.2023 |
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Reihe/Serie | Methods in Molecular Biology |
Zusatzinfo | 77 Illustrations, color; 11 Illustrations, black and white; XIII, 390 p. 88 illus., 77 illus. in color. |
Verlagsort | New York, NY |
Sprache | englisch |
Maße | 178 x 254 mm |
Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
Informatik ► Weitere Themen ► Bioinformatik | |
Naturwissenschaften ► Biologie ► Genetik / Molekularbiologie | |
Schlagworte | Artifical Intelligence • Computational Docking • genome databases • machine learning • Protein-protein complex databases • Text Mining |
ISBN-10 | 1-0716-2097-5 / 1071620975 |
ISBN-13 | 978-1-0716-2097-7 / 9781071620977 |
Zustand | Neuware |
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