ClusterM

ClusterM identifies conserved protein complexes across multiple Protein-Protein Interaction (PPI) networks by integrating network topology and protein sequence similarity for scalable comparative analysis.

Key Features:

• Integration of Network Topology and Sequence Similarity: Combines network topology information with protein sequence similarity data to improve detection of conserved protein complexes.
• Scalability and Efficiency: Mitigates exponential complexity growth when analyzing multiple PPI networks, enabling large-scale analyses.
• Topological Separability and Cohesive Conservation: Detects complexes that are densely connected internally yet distinct from other network components while preserving cohesive sequence conservation.

Scientific Applications:

• De novo conserved complex identification: Identifies conserved protein complexes across species including Saccharomyces cerevisiae, Drosophila melanogaster, Caenorhabditis elegans, and Homo sapiens.
• Evolutionary conservation analysis: Captures topological properties relevant to studying conservation of protein complexes across species.
• Functional genomics and systems biology: Supports analysis of complex-level functional modules within and across PPI networks for systems-level studies.

Methodology:

ClusterM integrates network topology and protein sequence similarity within an algorithmic framework to model PPI network structure and identify conserved protein complexes across multiple PPI networks.