title: Artificial ants deposit pheromone to search for regulatory DNA elements.
abstract: BACKGROUND
  Identification of transcription-factor binding motifs (DNA sequences) can be formulated as a combinatorial problem, where an efficient algorithm is indispensable to predict the role of multiple binding motifs. An ant algorithm is a biology-inspired computational technique, through which a combinatorial problem is solved by mimicking the behavior of social insects such as ants. We developed a unique version of ant algorithms to select a set of binding motifs by considering a potential contribution of each of all random DNA sequences of 4- to 7-bp in length.
  
  
  RESULTS
  Human chondrogenesis was used as a model system. The results revealed that the ant algorithm was able to identify biologically known binding motifs in chondrogenesis such as AP-1, NFkappaB, and sox9. Some of the predicted motifs were identical to those previously derived with the genetic algorithm. Unlike the genetic algorithm, however, the ant algorithm was able to evaluate a contribution of individual binding motifs as a spectrum of distributed information and predict core consensus motifs from a wider DNA pool.
  
  
  CONCLUSIONS
  The ant algorithm offers an efficient, reproducible procedure to predict a role of individual transcription-factor binding motifs using a unique definition of artificial ants.
authors.affiliation: Division of Biostatistics, Department of Medicine, Center for Computational Biology and Bioinformatics, Indiana University--Purdue University Indianapolis, Indianapolis, IN 46202, USA. yunliu@iupui.edu
authors.forename: Yunlong
authors.initials: Y
authors.lastname: Liu
authors.forename: Hiroki
authors.initials: H
authors.lastname: Yokota
mesh_terms: D020121:5' Untranslated Regions / Q000235:genetics; D000465:Algorithms; D000818:Animals; D001000:Ants / Q000235:genetics*; D020219:Chondrogenesis / Q000235:genetics; D004247:DNA / Q000235:genetics*; D005786:Gene Expression Regulation; D006801:Humans; D008957:Models, Genetic; D010675:Pheromones / Q000235:genetics*; D012045:Regulatory Sequences, Nucleic Acid; D015203:Reproducibility of Results
chemical_list: D020121:5' Untranslated Regions; D010675:Pheromones; D004247:DNA