Document Detail


Tree-based position weight matrix approach to model transcription factor binding site profiles.
MedLine Citation:
PMID:  21912677     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Most of the position weight matrix (PWM) based bioinformatics methods developed to predict transcription factor binding sites (TFBS) assume each nucleotide in the sequence motif contributes independently to the interaction between protein and DNA sequence, usually producing high false positive predictions. The increasing availability of TF enrichment profiles from recent ChIP-Seq methodology facilitates the investigation of dependent structure and accurate prediction of TFBSs. We develop a novel Tree-based PWM (TPWM) approach to accurately model the interaction between TF and its binding site. The whole tree-structured PWM could be considered as a mixture of different conditional-PWMs. We propose a discriminative approach, called TPD (TPWM based Discriminative Approach), to construct the TPWM from the ChIP-Seq data with a pre-existing PWM. To achieve the maximum discriminative power between the positive and negative datasets, the cutoff value is determined based on the Matthew Correlation Coefficient (MCC). The resulting TPWMs are evaluated with respect to accuracy on extensive synthetic datasets. We then apply our TPWM discriminative approach on several real ChIP-Seq datasets to refine the current TFBS models stored in the TRANSFAC database. Experiments on both the simulated and real ChIP-Seq data show that the proposed method starting from existing PWM has consistently better performance than existing tools in detecting the TFBSs. The improved accuracy is the result of modelling the complete dependent structure of the motifs and better prediction of true positive rate. The findings could lead to better understanding of the mechanisms of TF-DNA interactions.
Authors:
Yingtao Bi; Hyunsoo Kim; Ravi Gupta; Ramana V Davuluri
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't     Date:  2011-09-02
Journal Detail:
Title:  PloS one     Volume:  6     ISSN:  1932-6203     ISO Abbreviation:  PLoS ONE     Publication Date:  2011  
Date Detail:
Created Date:  2011-09-13     Completed Date:  2011-12-29     Revised Date:  2013-03-07    
Medline Journal Info:
Nlm Unique ID:  101285081     Medline TA:  PLoS One     Country:  United States    
Other Details:
Languages:  eng     Pagination:  e24210     Citation Subset:  IM    
Affiliation:
Molecular and Cellular Oncogenesis Program, Center for Systems and Computational Biology, The Wistar Institute, Philadelphia, Pennsylvania, United States of America.
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MeSH Terms
Descriptor/Qualifier:
Base Sequence
Binding Sites
Chromatin Immunoprecipitation
Computational Biology / methods*
Nucleotide Motifs / genetics
Position-Specific Scoring Matrices*
Transcription Factors / metabolism*
Grant Support
ID/Acronym/Agency:
P30 CA010815/CA/NCI NIH HHS; R01HG003362/HG/NHGRI NIH HHS
Chemical
Reg. No./Substance:
0/Transcription Factors
Comments/Corrections

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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