NDLI: Predicting Binding Sites in the Mouse Genome

Content Provider	IEEE Xplore Digital Library
Author	Yi Sun Robinson, M. Adams, R. Davey, N. Rust, A.
Copyright Year	2007
Description	Author affiliation: Univ. of Hertfordshire, Hatfield (Yi Sun; Robinson, M.; Adams, R.; Davey, N.)
Abstract	The identification of cis-regulatory binding sites in DNA in multicellular eukaryotes is a particularly difficult problem in computational biology. To obtain a full understanding of the complex machinery embodied in genetic regulatory networks it is necessary to know both the identity of the regulatory transcription factors together with the location of their binding sites in the genome. We show that using an SVM together with data sampling, to integrate the results of individual algorithms specialised for the prediction of binding site locations, can produce significant improvements upon the original algorithms applied to the mouse genome. These results make more tractable the expensive experimental procedure of actually verifying the predictions.
Starting Page	476
Ending Page	481
File Size	1933869
Page Count	6
File Format	PDF
ISBN	9780769530697
DOI	10.1109/ICMLA.2007.28
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-12-13
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Fungi Sequences Machine learning algorithms Genomics DNA Machine learning Prediction algorithms Mice Bioinformatics
Content Type	Text
Resource Type	Article

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