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Bioinformatics Advance Access published online on May 27, 2005
Bioinformatics, doi:10.1093/bioinformatics/bti521
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© The Author (2005). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oupjournals.org
Received May 23, 2005
Revised May 25, 2005
Accepted May 25, 2005

Article

Quantifying optimal accuracy of local primary sequence bioinformatics methods

Daniel P. Aalberts 1*, Eric G. Daub 1, and Jesse W. Dill 1

1 Physics Department, Williams College, Williamstown, MA 01267, USA

* To whom correspondence should be addressed.
Daniel P. Aalberts, E-mail: aalberts{at}williams.edu


  Abstract

Motivation: Traditional bioinformatics methods scan primary sequences for local patterns. It is important to assess how accurate local primary sequence methods can be.

Results: We study the problem of donor pre-mRNA splice site recognition, where the sequence overlaps between real and decoy data sets can be quantified, exposing the intrinsic limitations of the performance of local primary sequence methods. We assess the accuracy of primary sequence methods generally by studying how they scale with dataset size and demonstrate that our new Primary Sequence Ranking methods have superior performance.

Availability: Our Primary Sequence Ranking analysis tools are available at http://rna.williams.edu/.


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