Motif Finding with Application to the Transcription Factor Binding Sites Problem

DNA sequencing of different species has resulted in the generation of huge amount of biological data. There is an increasing need to develop computational techniques to search for relevant information in the DNA data. Discovering motifs involves determining short sequence segments which have a high probability of repeated occurrences over many sequences in different species. Motifs are useful in finding transcription factor binding sites, transcriptional regulatory elements and so on. Transcription factor binding sites (TFBSs) is important for understanding the genetic regulatory system. Our method is based on the Ant Colony Optimization (ACO) and Gibbs sampling algorithm to discover DNA motifs (collections of TFBSs) in a set of DNA-sequences. We first applied an ACO algorithm to find a set of better candidate positions for the motif. The resultant positions are given as input to the Gibbs sampler method for calculating score for each sequence. Based on the score, motif for TF binding sites is identified. General Terms Bioinformatics, Pattern Recognition