Dragon Promoter Mapper (DPM): A Bayesian framework for modelling promoter structures

Rajesh Chowdhary; Sin Lam Tan; R. Ayesha Ali; Brent Boerlage; Limsoon Wong; Vladimir B. Bajic

doi:10.1093/bioinformatics/btl125

Dragon Promoter Mapper (DPM): A Bayesian framework for modelling promoter structures

Rajesh Chowdhary, Sin Lam Tan, R. Ayesha Ali, Brent Boerlage, Limsoon Wong, Vladimir B. Bajic^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

5 Scopus citations

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.

Original language	English (US)
Pages (from-to)	2310-2312
Number of pages	3
Journal	Bioinformatics
Volume	22
Issue number	18
DOIs	https://doi.org/10.1093/bioinformatics/btl125
State	Published - Sep 15 2006
Externally published	Yes

ASJC Scopus subject areas

Statistics and Probability
Biochemistry
Molecular Biology
Computer Science Applications
Computational Theory and Mathematics
Computational Mathematics

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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.",

author = "Rajesh Chowdhary and Tan, {Sin Lam} and Ali, {R. Ayesha} and Brent Boerlage and Limsoon Wong and Bajic, {Vladimir B.}",

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AU - Tan, Sin Lam

AU - Ali, R. Ayesha

AU - Boerlage, Brent

AU - Wong, Limsoon

AU - Bajic, Vladimir B.

PY - 2006/9/15

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AB - 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.

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ER -

Dragon Promoter Mapper (DPM): A Bayesian framework for modelling promoter structures

Abstract

ASJC Scopus subject areas

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