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Data Mining Techniques for the Life Sciences: Methods in Molecular Biology, cartea 2449

Editat de Oliviero Carugo, Frank Eisenhaber
en Limba Engleză Paperback – 6 mai 2023
This 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.
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Specificații

ISBN-13: 9781071620977
ISBN-10: 1071620975
Ilustrații: XIII, 390 p. 88 illus., 77 illus. in color.
Dimensiuni: 178 x 254 mm
Greutate: 0.7 kg
Ediția:3rd ed. 2022
Editura: Springer Us
Colecția Humana
Seria Methods in Molecular Biology

Locul publicării:New York, NY, United States

Cuprins

 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.


Textul de pe ultima copertă

This 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.

Caracteristici

Includes cutting-edge methods and protocols Provides step-by-step detail essential for reproducible results Contains key notes and implementation advice from the experts

Recenzii

From the reviews:
“The book consists of three parts with 22 chapters prepared by well-known experts from many countries. … book will be useful for students and researchers, such as biochemists, molecular biologists, and biotechnologists, who wish to get a condensed introduction to the world of biological databases and their applications related to various aspects of life science.” (G. Ya. Wiederschain, Biochemistry, Vol. 76 (4), 2011)
“Provides a comprehensive overview and reference for molecular biologists and bioinformaticians as to the goals and scope of each database in each category. … The chapters are well written and provide a good introduction to the addressed topics … . Each chapter is an interesting and informative read in itself … . Overall, this edited volume provides a good reference to the current state of bioinformatics-related databases and as an introduction to the more common machine-learning techniques in bioinformatics.” (Iddo Friedberg, The Quarterly Review of Biology, Vol. 86, December, 2011)