Data Mining for Systems Biology

Methods and Protocols

  • Hiroshi Mamitsuka
  • Charles DeLisi
  • Minoru Kanehisa

Part of the Methods in Molecular Biology book series (MIMB, volume 939)

Table of contents

  1. Front Matter
    Pages i-xii
  2. Koji Tsuda, Elisabeth Georgii
    Pages 1-8
  3. Willy Hugo, Wing-Kin Sung, See-Kiong Ng
    Pages 9-20
  4. Misael Mongiovì, Roded Sharan
    Pages 21-34
  5. Antti Larjo, Ilya Shmulevich, Harri Lähdesmäki
    Pages 35-45
  6. Timothy Hancock, Ichigaku Takigawa, Hiroshi Mamitsuka
    Pages 69-85
  7. Kenichiro Imai, Sikander Hayat, Noriyuki Sakiyama, Naoya Fujita, Kentaro Tomii, Arne Elofsson et al.
    Pages 115-140
  8. Peter D. Karp, Suzanne Paley, Tomer Altman
    Pages 183-200
  9. Jui-Hung Hung
    Pages 201-213
  10. Bolan Linghu, Eric A. Franzosa, Yu Xia
    Pages 215-232
  11. Tun-Hsiang Yang, Mark Kon, Charles DeLisi
    Pages 233-251
  12. Carla Kuiken, Hyejin Yoon, Werner Abfalterer, Brian Gaschen, Chienchi Lo, Bette Korber
    Pages 253-261
  13. Back Matter
    Pages 277-279

About this book

Introduction

The post-genomic revolution is witnessing the generation of petabytes of data annually, with deep implications ranging across evolutionary theory, developmental biology, agriculture, and disease processes. Data Mining for Systems Biology: Methods and Protocols, surveys and demonstrates the science and technology of converting an unprecedented data deluge to new knowledge and biological insight. The volume is organized around two overlapping themes, network inference and functional inference. Written in the highly successful Methods in Molecular Biology™ series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible protocols, and key tips on troubleshooting and avoiding known pitfalls.

 

Authoritative and practical, Data Mining for Systems Biology: Methods and Protocols also seeks to aid researchers in the further development of databases, mining and visualization systems that are central to the paradigm altering discoveries being made with increasing frequency.

Keywords

Functional Inference Network Inference genotype heterogeneous datasets metabolism nucleic acids phenotype post-genomic revolution protein-DNA Interactions protein-protein interactions

Editors and affiliations

  • Hiroshi Mamitsuka
    • 1
  • Charles DeLisi
    • 2
  • Minoru Kanehisa
    • 3
  1. 1., Institute for Chemical ResearchKyoto UniversityKyotoJapan
  2. 2.Dept. Biomedical EngineeringBoston UniversityBostonUSA
  3. 3.Inst. Chemical Research, Bioinformatics CenterKyoto UniversityUjiJapan

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-62703-107-3
  • Copyright Information Springer Science+Business Media New York 2013
  • Publisher Name Humana Press, Totowa, NJ
  • eBook Packages Springer Protocols
  • Print ISBN 978-1-62703-106-6
  • Online ISBN 978-1-62703-107-3
  • Series Print ISSN 1064-3745
  • Series Online ISSN 1940-6029
  • About this book
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