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BMCBI
2011

RegNetB: Predicting Relevant Regulator-Gene Relationships in Localized Prostate Tumor Samples

7 years 8 months ago
RegNetB: Predicting Relevant Regulator-Gene Relationships in Localized Prostate Tumor Samples
Background: A central question in cancer biology is what changes cause a healthy cell to form a tumor. Gene expression data could provide insight into this question, but it is difficult to distinguish between a gene that causes a change in gene expression from a gene that is affected by this change. Furthermore, the proteins that regulate gene expression are often themselves not regulated at the transcriptional level. Here we propose a Bayesian modeling framework we term RegNetB that uses mechanistic information about the gene regulatory network to distinguish between factors that cause a change in expression and genes that are affected by the change. We test this framework using human gene expression data describing localized prostate cancer progression. Results: The top regulatory relationships identified by RegNetB include the regulation of RLN1, RLN2, by PAX4, the regulation of ACPP (PAP) by JUN, BACH1 and BACH2, and the co-regulation of PGC and GDF15 by MAZ and TAF8. These target...
Angel Alvarez, Peter J. Woolf
Added 24 Aug 2011
Updated 24 Aug 2011
Type Journal
Year 2011
Where BMCBI
Authors Angel Alvarez, Peter J. Woolf
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