Cleavage site analysis using rule extraction from neural networks

Authors:
Yeun-Jin Cho;Hyeoncheol Kim
Affiliations:
Department of Computer Science Education, Korea University, Seoul, Korea;Department of Computer Science Education, Korea University, Seoul, Korea
Venue:
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
Year:
2005

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Abstract

In this paper, we demonstrate that the machine learning approach of rule extraction from a trained neural network can be successfully applied to SARS-coronavirus cleavage site analysis. The extracted rules predict cleavage sites better than consensus patterns. Empirical experiments are also shown.