Pre-mRNA Secondary Structure Prediction Aids Splice Site Prediction

Donald J. Patterson, Ken Yasuhara and Walter L. Ruzzo

Pacific Symposium on Biocomputing, Kauai, Hawaii, Jan., 2002, pp. 223-234.

Abstract:  Accurate splice site prediction is a critical component of any computational approach to gene prediction in higher organisms. Existing approaches generally use sequence-based models that capture local dependencies among nucleotides in a small window around the splice site. We present evidence that computationally predicted secondary structure of moderate length pre-mRNA subsequences contains information that can be exploited to improve acceptor splice site prediction beyond that possible with conventional sequence-based approaches. Both decision tree and support vector machine classifiers, using folding energy and structure metrics characterizing helix formation near the splice site, achieve a 5--10% reduction in error rate with a human data set. Based on our data, we hypothesize that acceptors preferentially exhibit short helices at the splice site.

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E-mail: ruzzo /at/ cs /dot/ washington /dot/ edu