Prediction Of The Correlation Of Triplet Transcription Factor Binding Sites Based On PWMSA

Regulatory elements around the gene can refer to specific transcription factor binding and affect the transcription level of DNA sequence features. As an important component of transcriptional regulation, transcription factor binding sites identification has become a hot topic at present. Accurate prediction, identification algorithm helps people to identify the objectives of different transcription factor genes, and then study transcription factor binding sites in the upstream regulatory region of the location of the impact of transcriptional regulation.This article is based on the position weight matrix scoring algorithm of correlation of triplet transcription factor binding sites prediction method. Since the position weight matrix scoring algorithm is mainly targeted at single base sites using conservative position weight matrix prediction of transcription factor binding sites. Although this method can quickly identify transcription factor binding sites, but the position weight matrix model assumptions: binding sites of the base sequence of the contribution of an independent and binding of transcription factors. However, recent experimental studies have proved this hypothesis is not complete and binding sites of interaction between base pairs, a common contribution to the affinity with the transcription factor. It should also be the same with the coding region in the non-coding region, that three consecutive bases encoded a protein, which research has more biological significance. This paper based on previous research, the position weight matrix scoring algorithm applied to the correlation of triplet, using position weight matrix forecast the transcription factor binding sites.The algorithm in this paper implemented by C++, through experiments to prove its feasibility and effectiveness, and the forecast has been adopted with the transcription factor binding sites compared with the exiting of three softwares, which have received a higher success rate of the forecast shows that recognition of the correlation of triplet transcription factor binding sites based on PWMSA and its prediction performance is superior to single-nucleotide weight matrix sites.