title: Graphical approach to weak motif recognition.
abstract: We address the weak motif recognition problem in DNA sequences, which extends the general motif recognition to more difficult cases, allowing more degenerations in motif instances. Several algorithms have earlier attempted to find weak motifs in DNA sequences but with limitations. In this paper, we propose a graph-based algorithm for weak motif detection, which uses dynamic programming approach to find cliques indicating motif instances. The experiments on synthetic datasets show that the algorithm finds weak motif instances more accurately and efficiently compared to earlier approaches. Its performances on real datasets in finding transcription factor binding sites are comparable with the existing techniques.
authors.affiliation: BioInformatics Research Center, School of Computer Engineering, Nanyang Technological University, 639798, Singapore. xyang@pmail.ntu.edu.sg
authors.forename: Xiao
authors.initials: X
authors.lastname: Yang
authors.forename: Jagath C
authors.initials: JC
authors.lastname: Rajapakse
mesh_terms: D000465:Algorithms; D020816:Amino Acid Motifs; D001665:Binding Sites; D008956:Models, Chemical; D015233:Models, Statistical; D011485:Protein Binding; D011506:Proteins / Q000737:chemistry*; D020539:Sequence Analysis, Protein / Q000379:methods*
chemical_list: D011506:Proteins