Accurate Prediction of Alternatively Spliced Cassette Exons Using Evolutionary Conservation Information and Logitlinear Model

Abstract

Accurate prediction of alternative splicing (AS) is important for understanding the mechanism of gene regulation and studying the pathogenesis of diseases. By analyzing the evolutionary conservation information in alternatively spliced cassette exons (SCEs), constitutively spliced exons (CSEs) and their flanking intronic regions, we found that the average conservation score (AConScore) distributions of SCEs are significantly different from those of CSEs. We further integrated these unique features into the logitlinear model, and constructed a classifier, named AEDetector, for distinguishing SCEs from CSEs. The five-fold cross validation results show that the sensitivity and specificity of AEDetector are higher than those recently reported on the same dataset.

The Identification of Human Cassette Exons based on SVM

“…Although sequencing of expressed sequence tags (ESTs) and microarray analysis are effective experimental methods for identification of alternative splicing events, the work also needs computational approaches, because of the experimental limitations. Another method of identifying alternative spliced events is based on the features of sequences and conservation information of the human and mouse genome [2][3][4]. But it also has defects because of some exons or splice sites are lacking of homology information.…”