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Available online at www.sciencedirect.com Computers and Chemical Engineering 32 (2008) 633649
 

Summary: Available online at www.sciencedirect.com
Computers and Chemical Engineering 32 (2008) 633649
Informative gene selection and design of regulatory
networks using integer optimization
E. Yanga, T. Maguirea, M.L. Yarmusha, I.P. Androulakisa,b,
a Biomedical Engineering Department, Rutgers University, 617 Bowser Road, Piscataway, NJ 08854, United States
b Chemical & Biochemical Engineering Department, Rutgers University, Piscataway, NJ 08854, United States
Received 16 June 2006; received in revised form 21 January 2007; accepted 22 January 2007
Available online 12 February 2007
Abstract
A central problem in bioinformatics and systems biology is the selection of appropriate models in a rational and systematic way. This funda-
mentally combinatorial problem can be readily formulated and addressed within an integer optimization framework. In this paper we examine two
such applications related to the identification of informative genes and the quantification of regulatory networks. We demonstrate how multiple
alternatives can be systematically derived and assess the information content of the proposed solutions.
2007 Elsevier Ltd. All rights reserved.
Keywords: Gene expression; Regulatory networks; Gene selection; Classification; Integer optimization
1. Introduction
The recent advances in high throughput gene expression anal-
ysis have sparked an ongoing revolution in modern biology
(Bowtell, 1999; Cheung et al., 1999; Kafatos, 2002; Lipshutz

  

Source: Androulakis, Ioannis (Yannis) - Biomedical Engineering Department & Department of Chemical and Biochemical Engineering, Rutgers University

 

Collections: Engineering; Biology and Medicine