Modeling of gene regulatory network dynamics using threshold logic.

Full Abstract

Gene regulation modeling is one of the most active research topics in systems biology. The aim of modeling gene regulation is to understand how individual genes function and interact with each other to create complex biological phenomena. In this paper we propose a novel gene regulatory model based on threshold logic. The approach is developed by a combination of threshold logic properties and perceptron learning techniques. This work does not focus on determination of the pair-wise interactions among genes. Instead, the objective of this work is to generate a model that will describe and predict phenomena associated with a biological system. The utility of the approach is demonstrated by modeling a cellular system of 50 genes. The model could effectively replicate both the steady state and the transient behavior of genes.

Author information

Author/s: Gowda, Tejaswi (T); Vrudhula, Sarma (S); Kim, Seungchan (S);

Affiliation: School of Computing and Informatics, Arizona State University, Tempe, Arizona, USA. tejaswi(-atsign-)asu.edu

Journal and publication information

Publication Type: Journal Article; Research Support, U.S. Gov't, Non-P.H.S.

Journal: Annals of the New York Academy of Sciences (Ann N Y Acad Sci), published in United States. (Language: eng)

Reference: 2009-Mar; vol 1158 (issue ) : pp 71-81

Dates: Created 2009/04/07; Completed 2009/04/20;

PMID: 19348633, status: MEDLINE (last retrieval date: 4/20/2009, IMS Date: 20 Apr 2009 00:00:00)

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

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