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Cleavage Site Analysis Using Rule Extraction from Neural Networks

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.

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Detalhes bibliográficos
Publicado no:Advances in Natural Computation
Main Authors: Cho, Yeun-Jin, Kim, Hyeoncheol
Formato: Artigo
Idioma:Inglês
Publicado em: 2005
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC7114972/
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/11539087_132
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