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Nucleic Acids Research Advance Access published online on June 18, 2007
Nucleic Acids Research, doi:10.1093/nar/gkm407
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© 2007 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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SplicePort—An interactive splice-site analysis tool

Rezarta Islamaj Dogan1,2,*, Lise Getoor1, W. John Wilbur2 and Stephen M. Mount3,4

1Computer Science Department, University of Maryland, College Park, Maryland, 20742, 2National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, 20894, 3Department of Cell Biology and Molecular Genetics and 4Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland 20742, USA

*To whom correspondence should be addressed. Tel: (301) 405 2717; Email: rezarta{at}cs.umd.edu

Received January 31, 2007. Revised April 18, 2007. Accepted May 3, 2007.

SplicePort is a web-based tool for splice-site analysis that allows the user to make splice-site predictions for submitted sequences. In addition, the user can also browse the rich catalog of features that underlies these predictions, and which we have found capable of providing high classification accuracy on human splice sites. Feature selection is optimized for human splice sites, but the selected features are likely to be predictive for other mammals as well. With our interactive feature browsing and visualization tool, the user can view and explore subsets of features used in splice-site prediction (either the features that account for the classification of a specific input sequence or the complete collection of features). Selected feature sets can be searched, ranked or displayed easily. The user can group features into clusters and frequency plot WebLogos can be generated for each cluster. The user can browse the identified clusters and their contributing elements, looking for new interesting signals, or can validate previously observed signals. The SplicePort web server can be accessed at http://www.cs.umd.edu/projects/SplicePort and http://www.spliceport.org.


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