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Modeling of Gene Regulatory Network Dynamics Using Threshold Logic
Author(s) -
Gowda Tejaswi,
Vrudhula Sarma,
Kim Seungchan
Publication year - 2009
Publication title -
annals of the new york academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.712
H-Index - 248
eISSN - 1749-6632
pISSN - 0077-8923
DOI - 10.1111/j.1749-6632.2008.03754.x
Subject(s) - gene regulatory network , computer science , systems biology , function (biology) , gene , replicate , biological network , computational biology , biological system , artificial intelligence , biology , genetics , mathematics , gene expression , statistics
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.