A Parallel Algorithm for Eukaryotic Promoter Recognition

Abstract

One of the interesting problems in Bioinformatics is finding transcription start site in a gene. In fact, finding this site which separate promoter region from coding sequence, actually will end to promoter prediction. This leads to activate or inactivate some parts of gene which plays an important role after being translated to protein sequence. While traditional methods are reliable ways for promoter prediction, because of the large number of sequences and too much of information, it is not possible to study these sequences by those methods. Although some of these sequences have been already recognized and their information has been stored in big databases like NCBI, there are some sequences which their promoter regions have not been identified yet. This research aimed to design a parallel algorithm for one of the known promoter prediction algorithms, Ohler. We attempt to reduce the response time of Ohler algorithm, consequently increases the number of test samples, and improves the accuracy of the algorithm. The experimental results show that we have succeeded to achieve our purpose.