A neuro-fuzzy inference system to infer gene-gene interactions based on recognition of microarray gene expression patterns
Journal
2007 IEEE Congress on Evolutionary Computation
Pages
904-910
Date Issued
2007
Author(s)
Abstract
A neuro-fuzzy inference system that recognizes the expression patterns of genes in microarray gene expression (MGE) data, called GeneCFE-ANFIS, is proposed to infer gene interactions. In this study, three primary features are utilized to extract genes' expression patterns and used as inputs to neuro-fuzzy inference system. The proposed algorithm learns expression patterns from the known genetic interactions, such as the interactions confirmed by qRT-PCR experiments or collected through text-mining technique by surveying previously published literatures, and then predicts other gene interactions according to the learned patterns. The proposed neuro-fuzzy inference system was applied to a public yeast MGE data set. Two simulations were conducted and checked against 112 pairs of qRT-PCR confirmed gene interactions and 77 TFs pairs collected from literature respectively to evaluate the performance of the proposed algorithm.
Type
conference paper