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A property-based analysis of human transcription factors
BACKGROUND: Transcription factors are essential proteins for regulating gene expression. This regulation depends upon specific features of the transcription factors, including how they interact with DNA, how they interact with each other, and how they are post-translationally modified. Reliable info...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4373352/ https://www.ncbi.nlm.nih.gov/pubmed/25890365 http://dx.doi.org/10.1186/s13104-015-1039-6 |
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author | Bahrami, Shahram Ehsani, Rezvan Drabløs, Finn |
author_facet | Bahrami, Shahram Ehsani, Rezvan Drabløs, Finn |
author_sort | Bahrami, Shahram |
collection | PubMed |
description | BACKGROUND: Transcription factors are essential proteins for regulating gene expression. This regulation depends upon specific features of the transcription factors, including how they interact with DNA, how they interact with each other, and how they are post-translationally modified. Reliable information about key properties associated with transcription factors will therefore be useful for data analysis, in particular of data from high-throughput experiments. RESULTS: We have used an existing list of 1978 human proteins described as transcription factors to make a well-annotated data set, which includes information on Pfam domains, DNA-binding domains, post-translational modifications and protein–protein interactions. We have then used this data set for enrichment analysis. We have investigated correlations within this set of features, and between the features and more general protein properties. We have also used the data set to analyze previously published gene lists associated with cell differentiation, cancer, and tissue distribution. CONCLUSIONS: The study shows that well-annotated feature list for transcription factors is a useful resource for extensive data analysis; both of transcription factor properties in general and of properties associated with specific processes. However, the study also shows that such analyses are easily biased by incomplete coverage in experimental data, and by how gene sets are defined. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13104-015-1039-6) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4373352 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-43733522015-03-26 A property-based analysis of human transcription factors Bahrami, Shahram Ehsani, Rezvan Drabløs, Finn BMC Res Notes Research Article BACKGROUND: Transcription factors are essential proteins for regulating gene expression. This regulation depends upon specific features of the transcription factors, including how they interact with DNA, how they interact with each other, and how they are post-translationally modified. Reliable information about key properties associated with transcription factors will therefore be useful for data analysis, in particular of data from high-throughput experiments. RESULTS: We have used an existing list of 1978 human proteins described as transcription factors to make a well-annotated data set, which includes information on Pfam domains, DNA-binding domains, post-translational modifications and protein–protein interactions. We have then used this data set for enrichment analysis. We have investigated correlations within this set of features, and between the features and more general protein properties. We have also used the data set to analyze previously published gene lists associated with cell differentiation, cancer, and tissue distribution. CONCLUSIONS: The study shows that well-annotated feature list for transcription factors is a useful resource for extensive data analysis; both of transcription factor properties in general and of properties associated with specific processes. However, the study also shows that such analyses are easily biased by incomplete coverage in experimental data, and by how gene sets are defined. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13104-015-1039-6) contains supplementary material, which is available to authorized users. BioMed Central 2015-03-14 /pmc/articles/PMC4373352/ /pubmed/25890365 http://dx.doi.org/10.1186/s13104-015-1039-6 Text en © Bahrami et al.; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Bahrami, Shahram Ehsani, Rezvan Drabløs, Finn A property-based analysis of human transcription factors |
title | A property-based analysis of human transcription factors |
title_full | A property-based analysis of human transcription factors |
title_fullStr | A property-based analysis of human transcription factors |
title_full_unstemmed | A property-based analysis of human transcription factors |
title_short | A property-based analysis of human transcription factors |
title_sort | property-based analysis of human transcription factors |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4373352/ https://www.ncbi.nlm.nih.gov/pubmed/25890365 http://dx.doi.org/10.1186/s13104-015-1039-6 |
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