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- Title
RegNetB: predicting relevant regulator-gene relationships in localized prostate tumor samples.
- Authors
Alvarez, Angel; Woolf, Peter J
- Abstract
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.
- Publication
BMC bioinformatics, 2011, Vol 12, p243
- ISSN
1471-2105
- Publication type
Journal Article
- DOI
10.1186/1471-2105-12-243