Using a genetic algorithm to find promoter and motif

Identifying transcription factor binding sites in genes is an important problem in biology. To predict the binding site locations efficiently, many algorithms have been developed. However, the prediction accuracy is not satisfactory and binding site prediction thus remains a challenging problem. In this promotional article, we introduce develop an approach that can be used to predict binding site promoters using a genetic algorithm. Based on the generic framework of a genetic algorithm, the approach explores the search space of all possible starting locations of the binding site promoters and motifs in different target sequences with a population that undergoes evolution. Individuals in the population compete to participate in the crossovers and mutations occur with a certain probability. Initial experiments demonstrated that our approach could achieve high prediction accuracy in a small amount of computation time. A promising advantage of our approach is the fact that the computation time does not explicitly depend on the length of target sequences and hence may not increase significantly when the target sequences become very long. To avoid the exhaustive search, many computational tools have been developed to identify the common binding sites of homologous genes based on the stochastic Gibbs sampling algorithm that we used in this paper

کلیدواژه ها:

Evulution algorithm ، Genetic Algorithm ، Promoter ، Genome