Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/71493
Title: Prediction models for DNA transcription termination based on SOM networks
Authors: Bajic, V.B.
Charn, T.H.
Xu, J.X. 
Panda, S.K. 
Krishnan, S.P.T.
Keywords: Bioinfomatics
Polyadenylation sites
Self-organizing maps
Transcription termination
Issue Date: 2005
Citation: Bajic, V.B.,Charn, T.H.,Xu, J.X.,Panda, S.K.,Krishnan, S.P.T. (2005). Prediction models for DNA transcription termination based on SOM networks. Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings 7 VOLS : 4791-4794. ScholarBank@NUS Repository.
Abstract: This paper presents two efficient models for predicting transcription termination (TT) in human DNA. A neural network, Self-Organizing Map, was used for finding features from a human polyadenylation (polyA) sites dataset. We derived prediction models related to different polyA signals. A program, "Dragon PolyAtt", for predicting TT regions was designed for the two most frequent polyA sites "AAUAAA" and "AUUAAA". In our tests, Dragon PolyAtt predicts TT regions with a sensitivity of 48.4% (13.6%) and specificity of 74% (79.1%) when searching for polyA signal "AAUAAA" ("AUUAAA"). Both tests were done on human chromosome 21. Results of Dragon PolyAtt system are substantially better than those obtained by the well-known "polyadq" program. © 2005 IEEE.
Source Title: Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
URI: http://scholarbank.nus.edu.sg/handle/10635/71493
ISBN: 0780387406
ISSN: 05891019
Appears in Collections:Staff Publications

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