Network embedding framework for driver gene discovery by combining functional and structural information.

ABSTRACT: Comprehensive analysis of multiple data sets can identify potential driver genes for various cancers. In recent years, driver gene discovery based on massive mutation data and gene interaction networks has attracted increasing attention, but there is still a need to explore combining functional and structural information of genes in protein interaction networks to identify driver genes. Therefore, we propose a network embedding framework combining functional and structural information to identify driver genes. Firstly, we combine the mutation data and gene interaction networks to construct mutation integration network using network propagation algorithm. Secondly, the struc2vec model is used for extracting gene features from the mutation integration network, which contains both gene's func

SUBMITTER: Chu X 

PROVIDER: S-EPMC10386255 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature