Paper Info
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.http://defiant.i2r.a-star.edu.sg/projects/BayesPromoter/vlad@sanbi.ac.zaManual for using DPM web server is provided at http://defiant.i2r.a-star.edu.sg/projects/BayesPromoter/html/manual/manual.htm.
Year
DOI
Venue
2006
10.1093/bioinformatics/btl125
Bioinformatics
Keywords
Field
DocType
adjacent motif,dpm web server,bayesian framework,motif feature,motif occurrence,target promoter group,target promoter,modelling promoter structure,model promoter structure,target promoter sequence,bayesian network,dragon promoter mapper,genome sequence
Data mining,Promoter,Computer science,Motif (music),Bayesian network,Bioinformatics,Enhancer,Web server,Bayesian probability
Journal
Volume
Issue
ISSN
22
18
1367-4811
Citations 
PageRank 
References 
3
0.49
8
Authors
6
Name
Order
Citations
PageRank
Rajesh Chowdhary11005.94
Sin Lam Tan2584.17
R. Ayesha Ali3182.92
Brent Boerlage4162.89
Limsoon Wong53628638.37
Vladimir B. Bajic632133.71