title: An ant colony optimization based algorithm for identifying gene regulatory elements.
abstract: It is one of the most important tasks in bioinformatics to identify the regulatory elements in gene sequences. Most of the existing algorithms for identifying regulatory elements are inclined to converge into a local optimum, and have high time complexity. Ant Colony Optimization (ACO) is a meta-heuristic method based on swarm intelligence and is derived from a model inspired by the collective foraging behavior of real ants. Taking advantage of the ACO in traits such as self-organization and robustness, this paper designs and implements an ACO based algorithm named ACRI (ant-colony-regulatory-identification) for identifying all possible binding sites of transcription factor from the upstream of co-expressed genes. To accelerate the ants' searching process, a strategy of local optimization is presented to adjust the ants' start positions on the searched sequences. By exploiting the powerful optimization ability of ACO, the algorithm ACRI can not only improve precision of the results, but also achieve a very high speed. Experimental results on real world datasets show that ACRI can outperform other traditional algorithms in the respects of speed and quality of solutions.
authors.affiliation: Department of Computer Science and Engineering, Southeast University, Nanjing 210096, China. yzliuwei@126.com
authors.forename: Wei
authors.initials: W
authors.lastname: Liu
authors.forename: Hanwu
authors.initials: H
authors.lastname: Chen
authors.forename: Ling
authors.initials: L
authors.lastname: Chen
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001483:Base Sequence; D001665:Binding Sites; D002097:C-Reactive Protein / Q000737:chemistry / Q000235:genetics / Q000378:metabolism; D019295:Computational Biology / Q000379:methods*; D029968:Escherichia coli Proteins / Q000737:chemistry / Q000235:genetics / Q000378:metabolism; D053263:Gene Regulatory Networks; D006801:Humans; D008954:Models, Biological; D008969:Molecular Sequence Data; D015203:Reproducibility of Results; D029701:Saccharomyces cerevisiae Proteins / Q000737:chemistry / Q000235:genetics / Q000378:metabolism; D017422:Sequence Analysis, DNA / Q000379:methods*; D014157:Transcription Factors / Q000737:chemistry / Q000235:genetics / Q000378:metabolism
chemical_list: D029968:Escherichia coli Proteins; D029701:Saccharomyces cerevisiae Proteins; D014157:Transcription Factors; D002097:C-Reactive Protein