Causal inference of regulator-target pairs by gene mapping of expression phenotypes
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* Corresponding author: David C Kulp dkulp@cs.umass.edu
BMC Genomics 2006, 7:125 doi:10.1186/1471-2164-7-125
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BioMed Central: 4 citations
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Research article
Inferring causal genomic alterations in breast cancer using gene expression data Linh M Tran, Bin Zhang, Zhan Zhang, Chunsheng Zhang, Tao Xie, John R Lamb, Hongyue Dai, Eric E Schadt, Jun Zhu BMC Systems Biology 2011, 5:121 (1 August 2011) Systematic identification of causal copy number variations (CNVs) in breast cancer gene expression data using a wavelet based method to distinguish "driver genes" from "passenger genes" identifies known oncogenes and novel susceptibility genes.
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Methodology article
Disentangling molecular relationships with a causal inference test Joshua Millstein, Bin Zhang, Jun Zhu, Eric E Schadt BMC Genetics 2009, 10:23 (27 May 2009) |
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Methodology article
Using genetic markers to orient the edges in quantitative trait networks: The NEO software Jason E Aten, Tova F Fuller, Aldons J Lusis, Steve Horvath BMC Systems Biology 2008, 2:34 (15 April 2008) |
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Method
Harnessing naturally randomized transcription to infer regulatory relationships among genes Lin S Chen, Frank Emmert-Streib, John D Storey Genome Biology 2007, 8:R219 (11 October 2007) An approach is developed that utilizes randomized genotypes to rigorously infer causal regulatory relationships among genes at the transcriptional level. The approach is applied to an experiment in yeast, yielding new insights into the topology of the yeast transcriptional regulatory network. |