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A Generic Connectionist-Based Method for On-Line Feature Selection and Modelling with a Case Study of Gene Expression Data Analysis

Kasabov, N., Middlemiss, M. and Lane, T.

    The paper presents a novel generic method for on-line feature extraction from an incrementally trained connectionist system. The method is applied on a case study problem of identifying genes related to classes of diseases, in particular - 14 types of cancer. The method is based on the evolving connectionist systems ECOS paradigm. The analysis of the discovered features through the application of the proposed method on the case study data, demonstrates the potential of the method for solving important real world problems, such as the problem of defining genes related to diseases.
Cite as: Kasabov, N., Middlemiss, M. and Lane, T. (2003). A Generic Connectionist-Based Method for On-Line Feature Selection and Modelling with a Case Study of Gene Expression Data Analysis. In Proc. First Asia-Pacific Bioinformatics Conference (APBC2003), Adelaide, Australia. CRPIT, 19. Chen, Y.-P. P., Ed. ACS. 199-202.
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