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Predicting Transcription Factor Complexes

A Novel Approach to Data Integration in Systems Biology

  • Thorsten Will

Part of the BestMasters book series (BEST)

Table of contents

  1. Front Matter
    Pages I-XIX
  2. Thorsten Will
    Pages 1-23
  3. Thorsten Will
    Pages 25-43
  4. Thorsten Will
    Pages 45-87
  5. Thorsten Will
    Pages 89-110
  6. Thorsten Will
    Pages 111-112
  7. Back Matter
    Pages 113-142

About this book

Introduction

In his master thesis Thorsten Will proposes the substantial information content of protein complexes involving transcription factors in the context of gene regulatory  networks, designs the first computational approaches to predict such complexes as well as their regulatory function and verifies the practicability using data of the well-studied yeast S.cereviseae. The novel insights offer extensive capabilities towards a better understanding of the combinatorial control driving transcriptional regulation.

Contents

  • Protein Complex Prediction
  • Protein-Protein Interaction Networks
  • Domain-Domain Interaction Networks
  • Combinatorial Algorithms
  • Algorithm Engineering

 Target Groups

  • Computational biologists and biologists working with gene regulatory networks
  • Computer scientists interested in biological issues

 The Author

Currently, the author is pursuing his Ph.D. at the Center for Bioinformatics in Saarbrücken, Germany.

 

Keywords

Bioinformatics Gene Regulatory Networks Graph Algorithms Protein Complexes Transcriptional Regulation

Authors and affiliations

  • Thorsten Will
    • 1
  1. 1.Center of Bioinformatics/ Chair of Computational Biologyc/o Saarland UniversitySaarbrückenGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-658-08269-7
  • Copyright Information Springer Fachmedien Wiesbaden 2015
  • Publisher Name Springer Spektrum, Wiesbaden
  • eBook Packages Behavioral Science
  • Print ISBN 978-3-658-08268-0
  • Online ISBN 978-3-658-08269-7
  • Buy this book on publisher's site
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