BMRF-Net

BMRF-Net identifies protein interaction subnetworks by applying a bagging Markov random field (BMRF) framework to integrated gene expression and protein-protein interaction data for analysis of molecular mechanisms in disease.

Key Features:

• Bagging Markov random field (BMRF) framework: Implements a bagging Markov random field (BMRF) approach for subnetwork identification.
• Data integration: Integrates gene expression data with protein-protein interaction (PPI) data to inform subnetwork detection.
• Subnetwork detection: Identifies protein interaction subnetworks relevant to underlying molecular processes.
• Implementation: Implemented in Java and C++.

Scientific Applications:

• Breast cancer recurrence analysis: Applied to identify subnetworks associated with breast cancer recurrence.
• Disease mechanism investigation: Used to explore protein interaction networks implicated in disease-related molecular mechanisms.

Methodology:

Employs a bagging Markov random field (BMRF) framework that integrates gene expression data with protein-protein interaction data; implemented in Java and C++.