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A neuro-fuzzy approach for functional genomics data interpretation and analysis

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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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Authors and Affiliations

  1. Department of Computing, University of Bradford, Bradford, BD7 1DP, UK

    Daniel Neagu

  2. Computing Laboratory, Oxford University, Parks Road, Oxford, OX1 3QD, UK

    Vasile Palade

Authors
  1. Daniel Neagu
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  2. Vasile Palade
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Correspondence to Daniel Neagu.

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Neagu, D., Palade, V. A neuro-fuzzy approach for functional genomics data interpretation and analysis. Neural Comput & Applic 12, 153–159 (2003). https://doi.org/10.1007/s00521-003-0388-6

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  • DOI: https://doi.org/10.1007/s00521-003-0388-6

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