iDBPs: a web server for the identification of DNA binding proteins
The iDBPs server uses the three-dimensional (3D) structure of a query protein to predict whether it binds DNA. First, the algorithm predicts the functional region of the protein based on its evolutionary profile; the assumption is that large clusters of conserved residues are good markers of functio...
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Published in | Bioinformatics Vol. 26; no. 5; pp. 692 - 693 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
Oxford
Oxford University Press
01.03.2010
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Subjects | |
Online Access | Get full text |
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Summary: | The iDBPs server uses the three-dimensional (3D) structure of a query protein to predict whether it binds DNA. First, the algorithm predicts the functional region of the protein based on its evolutionary profile; the assumption is that large clusters of conserved residues are good markers of functional regions. Next, various characteristics of the predicted functional region as well as global features of the protein are calculated, such as the average surface electrostatic potential, the dipole moment and cluster-based amino acid conservation patterns. Finally, a random forests classifier is used to predict whether the query protein is likely to bind DNA and to estimate the prediction confidence. We have trained and tested the classifier on various datasets and shown that it outperformed related methods. On a dataset that reflects the fraction of DNA binding proteins (DBPs) in a proteome, the area under the ROC curve was 0.90. The application of the server to an updated version of the N-Func database, which contains proteins of unknown function with solved 3D-structure, suggested new putative DBPs for experimental studies. Availability: http://idbps.tau.ac.il/ Contact: NirB@tauex.tau.ac.il Supplementary information: Supplementary data are available at Bioinformatics online. |
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Bibliography: | ArticleID:btq019 To whom correspondence should be addressed. Associate Editor: Burkhard Rost istex:C52E205EB00E42486C71C44D39137DB4AA1C5064 ark:/67375/HXZ-4L5KH6K1-5 ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 1367-4803 1460-2059 1367-4811 |
DOI: | 10.1093/bioinformatics/btq019 |