Prognostic gene signature identification using causal structure learning: applications in kidney cancer.
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ABSTRACT:
SUBMITTER: Ha MJ
PROVIDER: S-EPMC4362630 | biostudies-literature | 2015
REPOSITORIES: biostudies-literature
Publications
Prognostic gene signature identification using causal structure learning: applications in kidney cancer.
Ha Min Jin MJ Baladandayuthapani Veerabhadran V Do Kim-Anh KA
Cancer informatics 20150127 Suppl 1
Identification of molecular-based signatures is one of the critical steps toward finding therapeutic targets in cancer. In this paper, we propose methods to discover prognostic gene signatures under a causal structure learning framework across the whole genome. The causal structures are represented by directed acyclic graphs (DAGs), wherein we construct gene-specific network modules that constitute a gene and its corresponding regulators. The modules are then subsequently used to correlate with ...[more]
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