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“Upstream Analysis”: An Integrated Promoter-Pathway Analysis Approach to Causal Interpretation of Microarray Data
A strategy is presented that allows a causal analysis of co-expressed genes, which may be subject to common regulatory influences. A state-of-the-art promoter analysis for potential transcription factor (TF) binding sites in combination with a knowledge-based analysis of the upstream pathway that co...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4996392/ https://www.ncbi.nlm.nih.gov/pubmed/27600225 http://dx.doi.org/10.3390/microarrays4020270 |
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author | Koschmann, Jeannette Bhar, Anirban Stegmaier, Philip Kel, Alexander E. Wingender, Edgar |
author_facet | Koschmann, Jeannette Bhar, Anirban Stegmaier, Philip Kel, Alexander E. Wingender, Edgar |
author_sort | Koschmann, Jeannette |
collection | PubMed |
description | A strategy is presented that allows a causal analysis of co-expressed genes, which may be subject to common regulatory influences. A state-of-the-art promoter analysis for potential transcription factor (TF) binding sites in combination with a knowledge-based analysis of the upstream pathway that control the activity of these TFs is shown to lead to hypothetical master regulators. This strategy was implemented as a workflow in a comprehensive bioinformatic software platform. We applied this workflow to gene sets that were identified by a novel triclustering algorithm in naphthalene-induced gene expression signatures of murine liver and lung tissue. As a result, tissue-specific master regulators were identified that are known to be linked with tumorigenic and apoptotic processes. To our knowledge, this is the first time that genes of expression triclusters were used to identify upstream regulators. |
format | Online Article Text |
id | pubmed-4996392 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-49963922016-09-06 “Upstream Analysis”: An Integrated Promoter-Pathway Analysis Approach to Causal Interpretation of Microarray Data Koschmann, Jeannette Bhar, Anirban Stegmaier, Philip Kel, Alexander E. Wingender, Edgar Microarrays (Basel) Article A strategy is presented that allows a causal analysis of co-expressed genes, which may be subject to common regulatory influences. A state-of-the-art promoter analysis for potential transcription factor (TF) binding sites in combination with a knowledge-based analysis of the upstream pathway that control the activity of these TFs is shown to lead to hypothetical master regulators. This strategy was implemented as a workflow in a comprehensive bioinformatic software platform. We applied this workflow to gene sets that were identified by a novel triclustering algorithm in naphthalene-induced gene expression signatures of murine liver and lung tissue. As a result, tissue-specific master regulators were identified that are known to be linked with tumorigenic and apoptotic processes. To our knowledge, this is the first time that genes of expression triclusters were used to identify upstream regulators. MDPI 2015-05-21 /pmc/articles/PMC4996392/ /pubmed/27600225 http://dx.doi.org/10.3390/microarrays4020270 Text en © 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Koschmann, Jeannette Bhar, Anirban Stegmaier, Philip Kel, Alexander E. Wingender, Edgar “Upstream Analysis”: An Integrated Promoter-Pathway Analysis Approach to Causal Interpretation of Microarray Data |
title | “Upstream Analysis”: An Integrated Promoter-Pathway Analysis Approach to Causal Interpretation of Microarray Data |
title_full | “Upstream Analysis”: An Integrated Promoter-Pathway Analysis Approach to Causal Interpretation of Microarray Data |
title_fullStr | “Upstream Analysis”: An Integrated Promoter-Pathway Analysis Approach to Causal Interpretation of Microarray Data |
title_full_unstemmed | “Upstream Analysis”: An Integrated Promoter-Pathway Analysis Approach to Causal Interpretation of Microarray Data |
title_short | “Upstream Analysis”: An Integrated Promoter-Pathway Analysis Approach to Causal Interpretation of Microarray Data |
title_sort | “upstream analysis”: an integrated promoter-pathway analysis approach to causal interpretation of microarray data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4996392/ https://www.ncbi.nlm.nih.gov/pubmed/27600225 http://dx.doi.org/10.3390/microarrays4020270 |
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