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dc.contributor.authorKundrotas, Petras J.
dc.contributor.authorZhu, Zhengwei
dc.contributor.authorVakser, Ilya A.
dc.date.accessioned2014-04-15T20:54:15Z
dc.date.available2014-04-15T20:54:15Z
dc.date.issued2009-11-09
dc.identifier.citationKundrotas, Petras J, Zhengwei Zhu, and Ilya A Vakser. 2010. “GWIDD: Genome-Wide Protein Docking Database.” Nucleic Acids Research 38 (Database issue): D513–D517. http://dx.doi.org/10.1093/nar/gkp944
dc.identifier.urihttp://hdl.handle.net/1808/13521
dc.description.abstractStructural information on interacting proteins is important for understanding life processes at the molecular level. Genome-wide docking database is an integrated resource for structural studies of protein–protein interactions on the genome scale, which combines the available experimental data with models obtained by docking techniques. Current database version (August 2009) contains 25 559 experimental and modeled 3D structures for 771 organisms spanned over the entire universe of life from viruses to humans. Data are organized in a relational database with user-friendly search interface allowing exploration of the database content by a number of parameters. Search results can be interactively previewed and downloaded as PDB-formatted files, along with the information relevant to the specified interactions. The resource is freely available at http://gwidd.bioinformatics.ku.edu.
dc.description.sponsorshipFunding for open access charge: National Institutes of Health (R01 GM074255).
dc.publisherOxford University Press
dc.rightsThis is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
dc.rights.urihttp://creativecommons.org/licenses/by-nc/2.5/uk/
dc.titleGWIDD: Genome-wide protein docking database
dc.typeArticle
kusw.kuauthorKundrotas, Petras J.
kusw.kuauthorZhu, Zhengwei
kusw.kuauthorVakser, Ilya A.
kusw.kudepartmentCenter for Bioinformatics
kusw.kudepartmentDepartment of Molecular Biosiences
kusw.oastatusfullparticipation
dc.identifier.doi10.1093/nar/gkp944
kusw.oaversionScholarly/refereed, publisher version
kusw.oapolicyThis item meets KU Open Access policy criteria.
dc.rights.accessrightsopenAccess


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This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Except where otherwise noted, this item's license is described as: This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.