4.7 Article

Segmentation of DNA using simple recurrent neural network

期刊

KNOWLEDGE-BASED SYSTEMS
卷 26, 期 -, 页码 271-280

出版社

ELSEVIER
DOI: 10.1016/j.knosys.2011.09.001

关键词

Quasi-regular structure; Elman network; Segmentation of DNA; SARS; H1N1

资金

  1. National Science Council [NSC100-2221-E-002-234-MY3]

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We report the discovery of strong correlations between protein coding regions and the prediction errors when using the simple recurrent network to segment genome sequences. We are going to use SARS genome to demonstrate how we conduct training and derive corresponding results. The distribution of prediction error indicates how the underlying hidden regularity of the genome sequences and the results are consistent with the finding of biologists: predicated protein coding features of SARS genome. This implies that the simple recurrent network is capable of providing new features for further biological studies when applied on genome studies. The HA gene of influenza A subtype H1N1 is also analyzed in a similar way. (C) 2011 Elsevier B.V. All rights reserved.

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