Chapter 3. Finding Verified Edges in Genetic/Gene Networks: Bilayer Verification for Network Recovery in the Presence of Hidden Confounders

  1. Dr. Frank Emmert-Streib2,3 and
  2. Dr. Matthias Dehmer4
  1. Jason E. Aten

Published Online: 16 SEP 2008

DOI: 10.1002/9783527622818.ch3

Analysis of Microarray Data: A Network-Based Approach

Analysis of Microarray Data: A Network-Based Approach

How to Cite

Aten, J. E. (2008) Finding Verified Edges in Genetic/Gene Networks: Bilayer Verification for Network Recovery in the Presence of Hidden Confounders, in Analysis of Microarray Data: A Network-Based Approach (eds F. Emmert-Streib and M. Dehmer), Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim, Germany. doi: 10.1002/9783527622818.ch3

Editor Information

  1. 2

    University of Washington, Department of Biostatistics, University of Washington, Department of Genome Sciences, Seattle, WA 98195-5065, USA

  2. 3

    Stowers Institute for Medical Research, 1000 East 50th Street, Kansas City, MO 64110, USA

  3. 4

    Vienna University of Technology, Discrete Mathematics and Geometry, Wiedner Hauptstrasse 8–10/104, 1040 Vienna, Austria

Author Information

  1. University of California Los Angeles, Department of Biomathematics, David Gaffen School of Medicine, AV-617 Center for Health Sciences, Box 951766, Los Angeles, CA 90095-1766, USA

Publication History

  1. Published Online: 16 SEP 2008
  2. Published Print: 13 FEB 2008

ISBN Information

Print ISBN: 9783527318223

Online ISBN: 9783527622818

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Keywords:

  • DNA microarrays;
  • analysis;
  • genetic networks;
  • gene networks;
  • bilayer verification;
  • causal discovery;
  • Bayesian network learning algorithms;
  • novel algorithm;
  • RVL algorithm;
  • recursive v-structures;
  • learning structural equation models

Summary

This chapter contains sections titled:

  • Introduction: Gene and Genetic Networks

  • Background and Prior Theory

  • New Theory

  • Methods

  • Results and Further Application

  • References