| Popis: |
In the study of complex phenotypes, single gene markers can only provide limited insights into the manifestation of phenotype. Recent studies show that, when considered together, many proteins that are connected via physical and functional interactions exhibit significant differential expression with respect to various complex phenotypes, including cancers. Compared to single gene markers, these “coordinately dysregulated subnetworks” offer novel insights into the network dynamics of phenotype. However, the problem of identifying coordinately dysregulated subnetworks presents significant algorithmic challenges. In this thesis, we propose two algorithms, NetCover and Crane, to capture the coordination among multiple genes at a sample-specific resolution. For NetCover, we formulate coordinate dysregulation in the context of the well-known set-cover problem. On the other hand, for Crane, we propose a combinatorial formulation of coordinate dysregulation. Comprehensive experimental results on human colorectal cancer show that, when compared to existing algorithms, our proposed algorithms improve diagnosis of cancer and prediction of metastasis significantly. |
