IMI-driver

IMI-driver integrates multi-omics data into eight biological networks and applies Multi-view Collaborative Network Embedding to identify cancer driver genes.

Key Features:

• Multi-omics Integration: Integrates multi-omics data into eight biological networks capturing multi-level gene regulation.
• Multi-view Collaborative Network Embedding: Embeds gene regulation information from biological networks into a low-dimensional vector space.
• Pan-cancer Analysis: Performs pan-cancer analysis to confirm candidate genes as known or potential drivers.

Scientific Applications:

• Cancer Driver Gene Identification: Identifies cancer driver genes for early detection, effective therapy, and precision medicine of cancer.
• Cross-cancer Comparison: Applied to 29 cancer types from The Cancer Genome Atlas (TCGA) and validated against nine benchmark datasets.
• Cancer Development and Progression Research: Case studies of new positive genes suggest their roles in cancer development and progression.

Methodology:

IMI-driver applies Multi-view Collaborative Network Embedding to embed gene regulation information from eight biological networks into a low-dimensional vector space. The method was tested on 29 cancer types from TCGA and compared with nine other methods on nine benchmark datasets.