 Research articlePredicting combinatorial binding of transcription factors to regulatory elements in the human genome by association rule miningXochitl C Morgan1* 1 Institute for Cellular and Molecular Biology and Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas 78712-0159, USA 2 Department of Computer Science, The University of Texas at Austin, Austin, Texas 78712-0159, USA
BMC Bioinformatics 2007, 8:445doi:10.1186/1471-2105-8-445
Additional filesAdditional file 1: 83 transcription factors from TRANSFAC. A list of the 83 transcription factor position weight matrices from TRANSFAC used for this analysis. Format: DOC Size: 30KB Download file This file can be viewed with: Microsoft Word Viewer Additional file 2: Effects of repeat masking. Support, confidence A=>B, and confidence B=>A are highly correlated between hg17 without repeat masking and hg18 with repeat masking. Format: TIFF Size: 1.2MB Download file Additional file 3: The subsets "genomewide", "mouse", and "promoter". "Genomewide", "Promoter", and "Mouse" are defined as top 50% difference between confidence A=>B and confidence B=>A and P < 0.05 as measured by the hypergeometric distribution. Pairs indicated in bold have been verified in the literature. Format: DOC Size: 50KB Download file This file can be viewed with: Microsoft Word Viewer Additional file 4: Estimated Patser error rates for PWMs. Approximate overestimation rates of position weight matrices from Patser. Format: DOC Size: 78KB Download file This file can be viewed with: Microsoft Word Viewer |
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