CDAP

CDAP evaluates protein complex detection methods in protein-protein interaction (PPI) networks to quantify and compare algorithm performance across multiple PPI datasets and gold standards.

Key Features:

• Comprehensive Evaluation Metrics: Introduces new evaluation criteria alongside existing metrics to assess protein complex detection algorithms.
• Comparison Across Multiple Datasets and Standards: Ranks methods using four distinct PPI datasets and three gold standards.
• Integration and Customization: Integrates results from multiple detection methods and applies filters to refine detected clusters, including filtering by protein name (STRING ID) and constraints on the number of proteins per cluster.
• Extensibility: Supports inclusion of additional PPI datasets, gold standards, and detection methods.

Scientific Applications:

• Method benchmarking: Quantitatively compares and ranks protein complex detection algorithms across multiple PPI datasets and gold standards.
• Method validation: Validates novel detection methods against established methods and gold standards.
• Comparative analysis with custom data: Enables comparison of custom method results and datasets against published methods and standards.

Methodology:

Evaluates detection methods using predefined and newly introduced metrics (including measures such as accuracy, precision, and robustness), ranks methods across four PPI datasets and three gold standards, and applies filters such as STRING ID matching and cluster size constraints.