Abstract
The paper is concerned about the application of neuro-fuzzy techniques for the functional analysis of gene expression data from microarray experiments. The objective of this paper is to learn and predict functional classes of the E. coli genes using neuro-fuzzy based techniques, such as modular neuro and neuro-fuzzy networks. Methods of combining explicit and implicit knowledge in functional interpretation and analysis of gene expression data are proposed.
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