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3DTF: a web server for predicting transcription factor PWMs using 3D structure-based energy calculations

We present the webserver 3D transcription factor (3DTF) to compute position-specific weight matrices (PWMs) of transcription factors using a knowledge-based statistical potential derived from crystallographic data on protein–DNA complexes. Analysis of available structures that can be used to constru...

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Detalles Bibliográficos
Autores principales: Gabdoulline, R., Eckweiler, D., Kel, A., Stegmaier, P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3394331/
https://www.ncbi.nlm.nih.gov/pubmed/22693215
http://dx.doi.org/10.1093/nar/gks551
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author Gabdoulline, R.
Eckweiler, D.
Kel, A.
Stegmaier, P.
author_facet Gabdoulline, R.
Eckweiler, D.
Kel, A.
Stegmaier, P.
author_sort Gabdoulline, R.
collection PubMed
description We present the webserver 3D transcription factor (3DTF) to compute position-specific weight matrices (PWMs) of transcription factors using a knowledge-based statistical potential derived from crystallographic data on protein–DNA complexes. Analysis of available structures that can be used to construct PWMs shows that there are hundreds of 3D structures from which PWMs could be derived, as well as thousands of proteins homologous to these. Therefore, we created 3DTF, which delivers binding matrices given the experimental or modeled protein–DNA complex. The webserver can be used by biologists to derive novel PWMs for transcription factors lacking known binding sites and is freely accessible at http://www.gene-regulation.com/pub/programs/3dtf/.
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spelling pubmed-33943312012-07-30 3DTF: a web server for predicting transcription factor PWMs using 3D structure-based energy calculations Gabdoulline, R. Eckweiler, D. Kel, A. Stegmaier, P. Nucleic Acids Res Articles We present the webserver 3D transcription factor (3DTF) to compute position-specific weight matrices (PWMs) of transcription factors using a knowledge-based statistical potential derived from crystallographic data on protein–DNA complexes. Analysis of available structures that can be used to construct PWMs shows that there are hundreds of 3D structures from which PWMs could be derived, as well as thousands of proteins homologous to these. Therefore, we created 3DTF, which delivers binding matrices given the experimental or modeled protein–DNA complex. The webserver can be used by biologists to derive novel PWMs for transcription factors lacking known binding sites and is freely accessible at http://www.gene-regulation.com/pub/programs/3dtf/. Oxford University Press 2012-07 2012-06-11 /pmc/articles/PMC3394331/ /pubmed/22693215 http://dx.doi.org/10.1093/nar/gks551 Text en © The Author(s) 2012. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Articles
Gabdoulline, R.
Eckweiler, D.
Kel, A.
Stegmaier, P.
3DTF: a web server for predicting transcription factor PWMs using 3D structure-based energy calculations
title 3DTF: a web server for predicting transcription factor PWMs using 3D structure-based energy calculations
title_full 3DTF: a web server for predicting transcription factor PWMs using 3D structure-based energy calculations
title_fullStr 3DTF: a web server for predicting transcription factor PWMs using 3D structure-based energy calculations
title_full_unstemmed 3DTF: a web server for predicting transcription factor PWMs using 3D structure-based energy calculations
title_short 3DTF: a web server for predicting transcription factor PWMs using 3D structure-based energy calculations
title_sort 3dtf: a web server for predicting transcription factor pwms using 3d structure-based energy calculations
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3394331/
https://www.ncbi.nlm.nih.gov/pubmed/22693215
http://dx.doi.org/10.1093/nar/gks551
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