Table of contents

  1. Front Matter
    Pages i-xii
  2. Fundamentals

    1. Front Matter
      Pages 1-1
    2. Janna Hastings
      Pages 3-13 Open Access
    3. Paul D. Thomas
      Pages 15-24 Open Access
    4. Pascale Gaudet, Nives Škunca, James C. Hu, Christophe Dessimoz
      Pages 25-37 Open Access
  3. Making Gene Ontology Annotations

    1. Front Matter
      Pages 39-39
    2. Sylvain Poux, Pascale Gaudet
      Pages 41-54 Open Access
    3. Domenico Cozzetto, David T. Jones
      Pages 55-67 Open Access
    4. Ruth C. Lovering
      Pages 85-93 Open Access
  4. Evaluating Gene Ontology Annotations

    1. Front Matter
      Pages 95-95
    2. Nives Škunca, Richard J. Roberts, Martin Steffen
      Pages 97-109 Open Access
    3. Gemma L. Holliday, Rebecca Davidson, Eyal Akiva, Patricia C. Babbitt
      Pages 111-132 Open Access
    4. Iddo Friedberg, Predrag Radivojac
      Pages 133-146 Open Access
  5. Using the Gene Ontology

    1. Front Matter
      Pages 147-147
    2. Monica Munoz-Torres, Seth Carbon
      Pages 149-160 Open Access
    3. Catia Pesquita
      Pages 161-173 Open Access
    4. Sebastian Bauer
      Pages 175-188 Open Access
    5. Pascale Gaudet, Christophe Dessimoz
      Pages 189-205 Open Access
    6. Fran Supek, Nives Škunca
      Pages 207-220 Open Access

About this book

Introduction

This book is open access under a CC BY 4.0 license.

This book provides a practical and self-contained overview of the Gene Ontology (GO), the leading project to organize biological knowledge on genes and their products across genomic resources. Written for biologists and bioinformaticians, it covers the state-of-the-art of how GO annotations are made, how they are evaluated, and what sort of analyses can and cannot be done with the GO. In the spirit of the Methods in Molecular Biology book series, there is an emphasis throughout the chapters on providing practical guidance and troubleshooting advice. 
Authoritative and accessible, The Gene Ontology Handbook serves non-experts as well as seasoned GO users as a thorough guide to this powerful knowledge system.

Keywords

Bioinformatics GO annotations Enrichment analysis Computational predictions Gene function

Editors and affiliations

  • Christophe Dessimoz
    • 1
  • Nives Škunca
    • 2
  1. 1.Department of Genetics Evolution and EnvironmentUniversity College of LondonLondonUnited Kingdom
  2. 2.Department of Computer ScienceETH ZurichZurichSwitzerland

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4939-3743-1
  • Copyright Information The Editor(s) (if applicable) and The Author(s) 2017
  • Publisher Name Humana Press, New York, NY
  • eBook Packages Springer Protocols
  • Print ISBN 978-1-4939-3741-7
  • Online ISBN 978-1-4939-3743-1
  • Series Print ISSN 1064-3745
  • Series Online ISSN 1940-6029
  • About this book