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Discovering modulators of gene expression

Proteins that modulate the activity of transcription factors, often called modulators, play a critical role in creating tissue- and context-specific gene expression responses to the signals cells receive. GEM (Gene Expression Modulation) is a probabilistic framework that predicts modulators, their a...

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Detalles Bibliográficos
Autores principales: Babur, Özgün, Demir, Emek, Gönen, Mithat, Sander, Chris, Dogrusoz, Ugur
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2943625/
https://www.ncbi.nlm.nih.gov/pubmed/20466809
http://dx.doi.org/10.1093/nar/gkq287
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author Babur, Özgün
Demir, Emek
Gönen, Mithat
Sander, Chris
Dogrusoz, Ugur
author_facet Babur, Özgün
Demir, Emek
Gönen, Mithat
Sander, Chris
Dogrusoz, Ugur
author_sort Babur, Özgün
collection PubMed
description Proteins that modulate the activity of transcription factors, often called modulators, play a critical role in creating tissue- and context-specific gene expression responses to the signals cells receive. GEM (Gene Expression Modulation) is a probabilistic framework that predicts modulators, their affected targets and mode of action by combining gene expression profiles, protein–protein interactions and transcription factor–target relationships. Using GEM, we correctly predicted a significant number of androgen receptor modulators and observed that most modulators can both act as co-activators and co-repressors for different target genes.
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spelling pubmed-29436252010-09-22 Discovering modulators of gene expression Babur, Özgün Demir, Emek Gönen, Mithat Sander, Chris Dogrusoz, Ugur Nucleic Acids Res Computational Biology Proteins that modulate the activity of transcription factors, often called modulators, play a critical role in creating tissue- and context-specific gene expression responses to the signals cells receive. GEM (Gene Expression Modulation) is a probabilistic framework that predicts modulators, their affected targets and mode of action by combining gene expression profiles, protein–protein interactions and transcription factor–target relationships. Using GEM, we correctly predicted a significant number of androgen receptor modulators and observed that most modulators can both act as co-activators and co-repressors for different target genes. Oxford University Press 2010-09 2010-05-13 /pmc/articles/PMC2943625/ /pubmed/20466809 http://dx.doi.org/10.1093/nar/gkq287 Text en © The Author(s) 2010. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/2.5 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), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Computational Biology
Babur, Özgün
Demir, Emek
Gönen, Mithat
Sander, Chris
Dogrusoz, Ugur
Discovering modulators of gene expression
title Discovering modulators of gene expression
title_full Discovering modulators of gene expression
title_fullStr Discovering modulators of gene expression
title_full_unstemmed Discovering modulators of gene expression
title_short Discovering modulators of gene expression
title_sort discovering modulators of gene expression
topic Computational Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2943625/
https://www.ncbi.nlm.nih.gov/pubmed/20466809
http://dx.doi.org/10.1093/nar/gkq287
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