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This article is part of the supplement: Proceedings of the 23rd International Conference on Genome Informatics (GIW 2012)

Open Access Proceedings

Using potential master regulator sites and paralogous expansion to construct tissue-specific transcriptional networks

Martin Haubrock, Jie Li and Edgar Wingender*

Author Affiliations

Department of Bioinformatics, University Medical Center Göttingen, Goldschmidtstrasse 1, D-37077 Göttingen, Germany

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BMC Systems Biology 2012, 6(Suppl 2):S15  doi:10.1186/1752-0509-6-S2-S15

Published: 12 December 2012

Additional files

Additional file 1:

Network statistics. Given are the numbers of vertices (split by TF and nonTF genes) and edges in the transcriptional networks without or with expansion, for the reference network as well for the tissue-specific networks.

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Open Data

Additional file 2:

Prediction validations. In this file, plots of positive predictive value (PPV), true positive rate (TPR) and Specificity are given for all TFs where sufficient experimental data have been made available by the ENCODE project. Validation has been made in each case for all prediction profiles from the 1% top-ranking sites down to 100% of the predictions for conserved binding sites.

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Open Data

Additional file 3:

Revisited false positives. Venn diagrams of comparing independent experimental datasets for TFBSs within the -1kb regions with each other and the predictions done in this study.

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Open Data

Additional file 4:

Degree statistics. The table indicates the average out-degree and in-degree of TF genes as well as the average in-degree of nonTF genes (NTF) for both the reconstructed transcriptional networks (reference network and tissue-specific networks) as well as the transcriptional network expanded by related TFs. It also shows the ratios of the corrresponding values for the expanded and the non-expanded networks (eTN/TN).

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Open Data

Additional file 5:

Degree distributions of tissue-specific transcriptional networks. Inverse cumulative in- and out-degree distributions of the tissue-specific transcriptional networks (TTNs) before and after paralogous expansions.

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Open Data