NetBox

NetBox performs network analysis of human protein interaction and pathway data to identify functional modules and altered network regions in diseases such as glioblastoma multiforme (GBM).

Key Features:

• Implementation: Implemented in Java for computational analysis.
• Pre-loaded Human Interaction Network (HIN): Integrates human interaction data from Human Protein Reference Database (HPRD), Reactome, NCI-Nature Pathway Interaction (PID) Database, and MSKCC Cancer Cell Map into a pre-configured HIN.
• Functional module detection: Detects functional modules within the HIN and identifies modules that are significantly altered across samples.
• Pathway-level interpretation: Identifies and highlights modules involving signaling pathways and proteins such as p53, Rb, PI3K, and receptor protein kinases.
• Candidate driver gene nomination: Nominates potential driver genes and oncogenes, for example AGAP2/CENTG1, and detects modules related to processes like microtubule organization.

Scientific Applications:

• Cancer genomic analysis: Analysis of cancer alterations to reveal recurrently altered functional modules in glioblastoma multiforme (GBM).
• Driver gene discovery: Identification of putative oncogenes and candidate drivers such as AGAP2/CENTG1 linked to pathway activation (e.g., PI3K).
• Signaling pathway characterization: Mapping and interpretation of pathway-centric modules involving p53, Rb, PI3K, and receptor protein kinases.
• Cellular process analysis: Detection of altered modules associated with cellular processes such as microtubule organization.

Methodology:

Integrates HPRD, Reactome, NCI-Nature PID, and MSKCC Cancer Cell Map into a pre-loaded Human Interaction Network (HIN), detects functional modules within the network, identifies significantly altered modules across samples, and nominates candidate driver genes such as AGAP2/CENTG1.