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AFEGRN: Adaptive Fuzzy Evolutionary Gene Regulatory Network Re-construction Framework

Sehgal, M. S. B.; Gondal, I.; Dooley, L. and Coppel, R. (2006). AFEGRN: Adaptive Fuzzy Evolutionary Gene Regulatory Network Re-construction Framework. In: IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2006), 16-21 July 2006, Vancouver.

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Most of Gene Regulatory Network (GRN) studies are based on crisp and parametric algorithms, despite inherent fuzzy nature of gene co-regulation. This paper presents Adaptive Fuzzy Evolutionary GRN Reconstruction (AFEGRN) framework for modeling GRNs. The AFEGRN automatically determines model parameters, such as, number of clusters for fuzzy c-means using fuzzy-PBM index and Estimation of Gaussian Distribution Algorithm. The proposed strategy was tested for breast cancer and normal GRNs. The results conformed to biological knowledge and showed that most of cancer related GRN changes were caused by differentially expressed genes. This demonstrates effectiveness of AFEGRN to model any GRN.

Item Type: Conference Item
Extra Information: ISBN: 0-7803-9488-7
Academic Unit/Department: Mathematics, Computing and Technology > Computing & Communications
Mathematics, Computing and Technology
Interdisciplinary Research Centre: Centre for Research in Computing (CRC)
Item ID: 10566
Depositing User: Laurence Dooley
Date Deposited: 10 Apr 2008
Last Modified: 14 Jan 2016 16:54
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