Scalable approach for effective control of gene regulatory networks

Tan M., Alhajj R., POLAT F.

ARTIFICIAL INTELLIGENCE IN MEDICINE, vol.48, no.1, pp.51-59, 2010 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 48 Issue: 1
  • Publication Date: 2010
  • Doi Number: 10.1016/j.artmed.2009.10.002
  • Journal Name: ARTIFICIAL INTELLIGENCE IN MEDICINE
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.51-59
  • Keywords: Gene regulatory networks, Control policy, Scalability technique, Feature reduction, Probabilistic Boolean networks, Markov decision problems, BOOLEAN NETWORKS, EXTERNAL CONTROL, INTERVENTION, MODEL
  • Middle East Technical University Affiliated: Yes

Abstract

Objective: Interactions between genes are realized as gene regulatory networks (GRNs). The control of such networks is essential for investigating issues like different diseases. Control is the process of studying the states and behavior of a given system under different conditions. The system considered in this study is a gene regulatory network (GRN), and one of the most important aspects in the control of GRNs is scalability. Consequently, the objective of this study is to develop a scalable technique that facilitates the control of GRNs.