IMI-driver: Integrating multi-level gene networks and multi-omics for cancer driver gene identification.

ABSTRACT: The identification of cancer driver genes is crucial for early detection, effective therapy, and precision medicine of cancer. Cancer is caused by the dysregulation of several genes at various levels of regulation. However, current techniques only capture a limited amount of regulatory information, which may hinder their efficacy. In this study, we present IMI-driver, a model that integrates multi-omics data into eight biological networks and applies Multi-view Collaborative Network Embedding to embed the gene regulation information from the biological networks into a low-dimensional vector space to identify cancer drivers. We apply IMI-driver to 29 cancer types from The Cancer Genome Atlas (TCGA) and compare its performance with nine other methods on nine benchmark datasets. IMI-driver ou

SUBMITTER: Shi P 

PROVIDER: S-EPMC11379397 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature