Systematic detection of statistically overrepresented DNA motif association rules.

Systematic detection of statistically overrepresented DNA motif association rules. Research Abstract Details 

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Systematic detection of statistically overrepresented DNA motif association rules. Abstract Text:

Jane Marie Lin,Zhiping Weng,

DNA motifs, or cis-elements, are short nucleotide sequence patterns recognized by various transcription factors (TFs). In promoters, these TFs bind in a complex combinatorial manner in order to regulate the expression of a downstream gene. The combinatorial space is frequently large and difficult to manage since vertebrates have thousands of transcription factors and more than 20,000 genes. We introduce a computer program called CAYCE (Combinatorial AnalYsis of Cis-Elements) that systematically detects statistically overrepresented DNA motif association rules independent of Microarray information. CAYCE is an adaptation of the apriori algorithm traditionally used for association rule mining, but offers three significant advancements. (1) It analyzes multiple occurrences of an item, corresponding to multiple TF binding sites, (2) It compares results with a biologically relevant background, and (3), it provides p-values for straightforward statistical interpretation. CAYCE can be easily applied to any item-set data where the investigator is also interested in multiple occurrences of a single item, and/or overrepresentation of association rules compared with a background. Applying CAYCE to human promoters in 1% of the human genome, we discover that motif clusters containing five repetitions of SP1 are the most statistically significant.

Systematic detection of statistically overrepresented DNA motif association rules. Publishing Authors By Initials

JM Lin,Z Weng,

For similar proteins: transcription factors research abstracts see: proteins: transcription factors research

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MEDLINE DATE:

Systematic detection of statistically overrepresented DNA motif association rules. Journal Published:

PUBLICATION TYPE: Research Support, Non-U.S. Gov

Journal: Genome informatics. International Conference on Ge

VOLUME: 17

Page Numbers: 124-33

Journal Abbreviation:

ISSN: 0919-9454

DAY: 3

MONTH: 12

YEAR: 2006

Systematic detection of statistically overrepresented DNA motif association rules. Information

Number of References:

LANGUAGE: eng

NlmUniqueID: 101280573

Systematic detection of statistically overrepresented DNA motif association rules. Keywords Mesh Terms:

KEYWORDS: Transcription Factors

MESH TERMS: metabolism

Chemical & Substance for Abstract: Systematic detection of statistically overrepresented DNA motif association rules. Information

Substance Name: DNA

Registry Number: 9007-49-2

Grant and Affiliation Information for Systematic detection of statistically overrepresented DNA motif association rules.

AFFILIATION: Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA. janemlin@bu.edu

Country: Japan

AGENCY: United States NIGMS

GRANT: T32GM008764-06

ACRONYM: GM

MEDLINETA: Genome Inform

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