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2007
IEEE

Genetic Regulatory Network Modeling Using Network Component Analysis and Fuzzy Clustering

11 years 9 months ago
Genetic Regulatory Network Modeling Using Network Component Analysis and Fuzzy Clustering
Gene regulatory network model is the most widely used mechanism to model and predict the behavior of living organisms. Network Component Analysis (NCA) as an emerging issue for uncovering hidden regulatory signals, has attracted significant trends in the research community. The common scheme in NCA is to model the controlling behavior of some proteins on the expression value of genes. However, this modeling requires performing certain experiments which are expensive in terms of time and feasibility. In this paper, we employ simple and effective data mining algorithm to obtain a purely gene- to gene model which predicts the effect of certain genes on the whole system. In order to accomplish this goal we employ Fuzzy clustering and Mutual Information (MI) for determining regulator genes resulting in two methods named as: Mutual Information based NCA (MINCA) and Fuzzy based NCA (FNCA). Simulation results validated using Coefficient of Determination (CoD), show that our methods model the s...
Fatemeh Bakouie, Mohammad Hassan Moradi
Added 13 Aug 2010
Updated 13 Aug 2010
Type Conference
Year 2007
Where CIBCB
Authors Fatemeh Bakouie, Mohammad Hassan Moradi
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