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Data Mining Techniques for the Life Sciences

  • Book
  • © 2022

Overview

Editors:
  1. Oliviero Carugo

    1. University of Pavia, Pavia, Italy

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    You can also search for this editor in PubMed   Google Scholar

  2. Frank Eisenhaber

    1. Genome Institute and Bioinformatics Institute, Singapore, Singapore

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    You can also search for this editor in PubMed   Google Scholar

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

Part of the book series: Methods in Molecular Biology (MIMB, volume 2449)

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Table of contents (15 protocols)

  1. Front Matter

    Pages i-xiii
    Download chapter PDF

  2. Databases

    1. Front Matter

      Pages 1-1
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    2. Data Mining, Quality and Management in the Life Sciences

      • Amonida Zadissa, Rolf Apweiler
      Pages 3-25

    3. IMEx Databases: Displaying Molecular Interactions into a Single, Standards-Compliant Dataset

      • Pablo Porras, Sandra Orchard, Luana Licata
      Pages 27-42

    4. Three-dimensional Structure Databases of Biological Macromolecules

      • Vaishali P. Waman, Christine Orengo, Gerard J. Kleywegt, Arthur M. Lesk
      Pages 43-91

  3. Prediction Methods

    1. Front Matter

      Pages 93-93
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    2. Predicting Protein Conformational Disorder and Disordered Binding Sites

      • Ketty C. Tamburrini, Giulia Pesce, Juliet Nilsson, Frank Gondelaud, Andrey V. Kajava, Jean-Guy Berrin et al.
      Pages 95-147

    3. Profiles of Natural and Designed Protein-Like Sequences Effectively Bridge Protein Sequence Gaps: Implications in Distant Homology Detection

      • Gayatri Kumar, Narayanaswamy Srinivasan, Sankaran Sandhya
      Pages 149-167

    4. Turning Failures into Applications: The Problem of Protein ΔΔG Prediction

      • Rita Casadio, Castrense Savojardo, Piero Fariselli, Emidio Capriotti, Pier Luigi Martelli
      Pages 169-185

    5. Dissecting the Genome for Drug Response Prediction

      • Gerardo Pepe, Chiara Carrino, Luca Parca, Manuela Helmer-Citterich
      Pages 187-196

    6. Prediction of the Effect of pH on the Aggregation and Conditional Folding of Intrinsically Disordered Proteins with SolupHred and DispHred

      • Valentín Iglesias, Carlos Pintado-Grima, Jaime Santos, Marc Fornt, Salvador Ventura
      Pages 197-211

    7. Extracting the Dynamic Motion of Proteins Using Normal Mode Analysis

      • Jacob A. Bauer, Vladena Bauerová-Hlinková
      Pages 213-231

  5. Big Data

    1. Front Matter

      Pages 325-325
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    2. Computational Pipeline for Rational Drug Combination Screening in Patient-Derived Cells

      • Paschalis Athanasiadis, Aleksandr Ianevski, Sigrid S. SkÃ¥nland, Tero Aittokallio
      Pages 327-348

    3. Deep Mining from Omics Data

      • Abeer Alzubaidi, Jonathan Tepper
      Pages 349-386
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Keywords

About this book

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.

Editors and Affiliations

  • University of Pavia, Pavia, Italy

    Oliviero Carugo

  • Genome Institute and Bioinformatics Institute, Singapore, Singapore

    Frank Eisenhaber

Bibliographic Information

  • Book Title: Data Mining Techniques for the Life Sciences

  • Editors: Oliviero Carugo, Frank Eisenhaber

  • Series Title: Methods in Molecular Biology

  • DOI: https://doi.org/10.1007/978-1-0716-2095-3

  • Publisher: Humana New York, NY

  • eBook Packages: Springer Protocols

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature 2022

  • Hardcover ISBN: 978-1-0716-2094-6Published: 05 May 2022

  • Softcover ISBN: 978-1-0716-2097-7Published: 06 May 2023

  • eBook ISBN: 978-1-0716-2095-3Published: 04 May 2022

  • Series ISSN: 1064-3745

  • Series E-ISSN: 1940-6029

  • Edition Number: 3

  • Number of Pages: XIII, 390

  • Number of Illustrations: 11 b/w illustrations, 77 illustrations in colour

  • Topics: Bioinformatics

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