J M Claverie1, S Audic. 1. Structural and Genetic Information Laboratory, CNRS-E.P. 91, Institute of Structural Biology and Microbiology, Marseille, France. jmc@igs.cnrs-mrs.fr
Abstract
MOTIVATION: To improve the detection of nucleotide sequence signals (e.g. promoter elements) by position-weight matrices (PWM) using the concept of statistically significant matches. RESULTS: The Mksite program was originally developed for analyzing protein sequences. We report NMksite, a new version adapted to the processing of nucleotide sequences. NMksite creates PWM from nucleotide sequence block alignments or occurrence tables using three weight computation schemes. An original feature of NMksite is the numerical computation of the statistical significance of PWM matches. The utility of this concept is demonstrated in the context of the prediction of splice sites and promoter regions.
MOTIVATION: To improve the detection of nucleotide sequence signals (e.g. promoter elements) by position-weight matrices (PWM) using the concept of statistically significant matches. RESULTS: The Mksite program was originally developed for analyzing protein sequences. We report NMksite, a new version adapted to the processing of nucleotide sequences. NMksite creates PWM from nucleotide sequence block alignments or occurrence tables using three weight computation schemes. An original feature of NMksite is the numerical computation of the statistical significance of PWM matches. The utility of this concept is demonstrated in the context of the prediction of splice sites and promoter regions.