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Biological Sequence Mining Using Plausible Neural Network and its Application to Exon/intron Boundaries Prediction

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4 Author(s)
Kuochen Li ; CECS, University of Louisville, Louisville, KY 40292, USA ; Dar-jen Chang ; Eric Rouchka ; Yuan Yan Chen

Biological sequence usually contains yet to find knowledge, and mining biological sequences usually involves a huge dataset and long computation time. Common tasks for biological sequence mining are pattern discovery, classification and clustering. The newly developed model, plausible neural network (PNN), provides an intuitive and unified architecture for such a large dataset analysis. This paper introduces the basic concepts of the PNN, and explains how it is applied to biological sequence mining. The specific task of biological sequence mining, exon/intron prediction, is implemented by using PNN. The experimental results show the capability of solving biological sequence mining tasks using PNN

Published in:

Computational Intelligence and Bioinformatics and Computational Biology, 2007. CIBCB '07. IEEE Symposium on

Date of Conference:

1-5 April 2007