Clustering and detection of 5' splice sites of mRNA by k weight-matrices model.
We propose a novel method to detect 5' splice sites of eukaryotic mRNA. We have grouped the 5' splice splice sites into various classes. The clustered sites are represented by a set of PWMs. The clustering algorithm is similar to k-means clustering algorithm but the distance definition and the training score function were arranged. The clustered PWMs were applied to 5' splice site detection. The results showed an improvement in comparison with traditional single PWM. The result of the clusters suggests there are new motifs of 5' splice sites.
Murakami
K
K
Central Research Laboratory, Hitachi, Ltd., Tokyo, Japan.
Takagi
T
T
D000465:Algorithms; D001483:Base Sequence; D019295:Computational Biology / Q000379:methods; D003198:Computer Simulation; D016384:Consensus Sequence; D016208:Databases, Factual; D020407:Internet; D008957:Models, Genetic; D012326:RNA Splicing; D012333:RNA, Messenger / Q000737:chemistry* / Q000235:genetics*; D012680:Sensitivity and Specificity; D012984:Software
D012333:RNA, Messenger