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- W2018096105 abstract "Gene regulatory network gives the idea about the nature of interaction among the genes present in the DNA of a living species. Recently 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." @default.
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- W2018096105 date "2009-01-01" @default.
- W2018096105 modified "2023-09-25" @default.
- W2018096105 title "Extraction of interaction information among genes from gene expression time series data" @default.
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- W2018096105 doi "https://doi.org/10.1109/nabic.2009.5393607" @default.
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