title: Dragon Promoter Mapper (DPM): a Bayesian framework for modelling promoter structures.
abstract: Dragon Promoter Mapper (DPM) is a tool to model promoter structure of co-regulated genes using methodology of Bayesian networks. DPM exploits an exhaustive set of motif features (such as motif, its strand, the order of motif occurrence and mutual distance between the adjacent motifs) and generates models from the target promoter sequences, which may be used to (1) detect regions in a genomic sequence which are similar to the target promoters or (2) to classify other promoters as similar or not to the target promoter group. DPM can also be used for modelling of enhancers and silencers.
  
  
  BACKGROUND
  http://defiant.i2r.a-star.edu.sg/projects/BayesPromoter/
  
  
  BACKGROUND
  vlad@sanbi.ac.za
  
  
  BACKGROUND
  Manual for using DPM web server is provided at http://defiant.i2r.a-star.edu.sg/projects/BayesPromoter/html/manual/manual.htm.
authors.affiliation: Knowledge Extraction Lab, Institute for Infocomm Research 21 Heng Mui Keng Terrace, Singapore 119613, Singapore.
authors.forename: Rajesh
authors.initials: R
authors.lastname: Chowdhary
authors.forename: Sin Lam
authors.initials: SL
authors.lastname: Tan
authors.forename: R Ayesha
authors.initials: RA
authors.lastname: Ali
authors.forename: Brent
authors.initials: B
authors.lastname: Boerlage
authors.forename: Limsoon
authors.initials: L
authors.lastname: Wong
authors.forename: Vladimir B
authors.initials: VB
authors.lastname: Bajic
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D002874:Chromosome Mapping / Q000379:methods*; D003198:Computer Simulation; D008957:Models, Genetic; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods; D011401:Promoter Regions, Genetic / Q000235:genetics*; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software; D014584:User-Computer Interface