Please use this identifier to cite or link to this item: https://doi.org/10.1093/bioinformatics/btl125
Title: Dragon Promoter Mapper (DPM): A Bayesian framework for modelling promoter structures
Authors: Chowdhary, R.
Tan, S.L.
Ali, R.A.
Boerlage, B.
Wong, L. 
Bajic, V.B.
Issue Date: 2006
Source: Chowdhary, R., Tan, S.L., Ali, R.A., Boerlage, B., Wong, L., Bajic, V.B. (2006). Dragon Promoter Mapper (DPM): A Bayesian framework for modelling promoter structures. Bioinformatics 22 (18) : 2310-2312. ScholarBank@NUS Repository. https://doi.org/10.1093/bioinformatics/btl125
Abstract: Summary: 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. © 2006 Oxford University Press.
Source Title: Bioinformatics
URI: http://scholarbank.nus.edu.sg/handle/10635/39636
ISSN: 13674803
DOI: 10.1093/bioinformatics/btl125
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