Gene splice sites based on sequential pattern mining

Gene splicing as a tightly regulated process, is a pivotal process between transcription and translation during gene expression. Splice sites are the kernel regulatory elements for gene splicing. Here, based on the sequential features minded from splice site sequences, we develop a score system for splice site sequences. Through this score system, splice site sequence can be measured quantitatively. The experimental results show that the canonical and pseudo splice site sequences can be discriminated effectively. Moreover, this model outperforms the maximum information entropy model with a great robustness, and the pathogenic splice site sequence mutations can be detected efficiently by the model.