Regularized Multi-View Subspace Clustering for Common Modules Across Cancer Stages.

ABSTRACT: Discovering the common modules that are co-expressed across various stages can lead to an improved understanding of the underlying molecular mechanisms of cancers. There is a shortage of efficient tools for integrative analysis of gene expression and protein interaction networks for discovering common modules associated with cancer progression. To address this issue, we propose a novel regularized multi-view subspace clustering (rMV-spc) algorithm to obtain a representation matrix for each stage and a joint representation matrix that balances the agreement across various stages. To avoid the heterogeneity of data, the protein interaction network is incorporated into the objective of rMV-spc via regularization. Based on the interior point algorithm, we solve the optimization problem to obta

SUBMITTER: Zhang E 

PROVIDER: S-EPMC6102576 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature