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 Jul 2006, Vancouver.

DOI: https://doi.org/10.1109/FUZZY.2006.1681940

Abstract

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.

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About

• Item ORO ID
• 10566
• Item Type
• Conference or Workshop Item
• Extra Information
• ISBN: 0-7803-9488-7
• Academic Unit or School
• Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
  Faculty of Science, Technology, Engineering and Mathematics (STEM)
• Research Group
• Centre for Research in Computing (CRC)
• Depositing User
• Laurence Dooley