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Extraction of interaction information among genes from gene expression time series data

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3 Author(s)
Datta, D. ; Dept. of Inf. Technol., St. Thomas'' Coll. of Eng. & Technol., Kolkata, India ; Konar, A. ; Janarthanan, R.

Gene regulatory network gives the idea about the nature of interaction among the genes present in the DNA of a living species. Detection of gene regulatory network from gene expression data is of prime interest to the researchers. This paper considers modelling of the gene regulatory network identification problem using a fuzzy recurrent neural network, and obtains the interaction weights among the neuron using differential evolution algorithm. A cost function is designed, the minimization of which yields the solution to the problem. In order to improve the solution further, a heuristic based local search is proposed. Computer simulation of the proposed inference algorithm revels that it is able to predict the signs of all the existing weights accurately.

Published in:

Nature & Biologically Inspired Computing, 2009. NaBIC 2009. World Congress on

Date of Conference:

9-11 Dec. 2009

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