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From the third issue of 2017, Microarrays has changed its name to High-Throughput.

Open AccessArticle
Microarrays 2015, 4(2), 270-286; doi:10.3390/microarrays4020270

“Upstream Analysis”: An Integrated Promoter-Pathway Analysis Approach to Causal Interpretation of Microarray Data

1
Xplain GmbH, D-38302 Wolfenbüttel, Germany
2
Institute of Bioinformatics, University Medical Center Göttingen, D-37077 Göttingen, Germany
*
Author to whom correspondence should be addressed.
Academic Editor: Heather J. Ruskin
Received: 17 March 2015 / Revised: 11 May 2015 / Accepted: 14 May 2015 / Published: 21 May 2015
(This article belongs to the Special Issue Computational Modeling and Analysis of Microarray Data: New Horizons)
View Full-Text   |   Download PDF [993 KB, uploaded 21 May 2015]   |  

Abstract

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. View Full-Text
Keywords: microarray data; gene expression signatures; upstream analysis; promoter analysis; pathway analysis microarray data; gene expression signatures; upstream analysis; promoter analysis; pathway analysis
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Koschmann, J.; Bhar, A.; Stegmaier, P.; Kel, A.E.; Wingender, E. “Upstream Analysis”: An Integrated Promoter-Pathway Analysis Approach to Causal Interpretation of Microarray Data. Microarrays 2015, 4, 270-286.

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