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Extracting networks from expression data

Part 4. Bioinformatics

4.5. Computational Methods for High-throughput Genetic Analysis: Expression Profiling

Short Specialist Review

  1. Vassily Hatzimanikatis,
  2. Eleftherios T. Papoutsakis

Published Online: 15 NOV 2005

DOI: 10.1002/047001153X.g405309

Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics

Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics

How to Cite

Hatzimanikatis, V. and Papoutsakis, E. T. 2005. Extracting networks from expression data. Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics. 4:4.5:60.

Author Information

  1. Northwestern University, Evanston, IL, USA

Publication History

  1. Published Online: 15 NOV 2005

Abstract

We discuss the properties of some of the model-based identification methods used for the development of genetic networks from gene expression data. The performance of these methods is evaluated with respect to their ability to deal with different type of data, the dimensionality of the data, the combinatorial nature of gene expression regulation, and the mathematical representation of the genetic network. We identify several key issues that must be resolved in order to improve our ability to extract networks from expression data.

Keywords:

  • genetic networks;
  • regulatory networks;
  • identification methods;
  • mathematical models;
  • model-based methods;
  • linear models;
  • nonlinear models;
  • mixed-integer methods