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BIOINFORMATICS Vol. 00 no. 00 2004
 

Summary: BIOINFORMATICS
Vol. 00 no. 00 2004
Pages 16
Quantifying optimal accuracy of local primary
sequence bioinformatics methods
Daniel P. Aalberts, Eric G. Daub, Jesse W. Dill
Physics Department, Williams College, Williamstown, MA 01267, USA
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 intrin-
sic limitations of the performance of local primary sequence
methods. We assess the accuracy of primary sequence
methods generally by studying how they scale with data-
set size and demonstrate that our new Primary Sequence
Ranking methods have superior performance.
Availability: Our Primary Sequence Ranking analysis tools

  

Source: Aalberts, Daniel P. - Department of Physics, Williams College

 

Collections: Physics