cpdb

cpdb integrates molecular interaction and pathway data for Homo sapiens to provide a consolidated map of protein-protein interactions, genetic interactions, metabolic and signaling pathways, gene regulatory networks, drug-target interactions, and biochemical pathways for analysis of cellular processes.

Key Features:

• Extensive Interaction Database: Integrates data from 30 distinct databases and comprises 215,541 unique molecular interactions covering binary protein-protein interactions, genetic interactions, metabolic pathways, signaling cascades, gene regulatory networks, drug-target interactions, and biochemical pathways.
• Confidence Scoring (IntScore): Employs the IntScore mechanism to evaluate the reliability of binary protein interactions.
• Pathway Analysis for Metabolites: Performs pathway analysis tailored for metabolite lists.
• Gene Set Analysis by Protein Complexes: Conducts gene set analysis based on protein complexes.
• Induced Network Modules Analysis: Connects input gene lists through diverse interaction types to identify induced network modules.
• Visualization Methods: Provides visualization using overlap graphs for functional gene/metabolite sets and implements graph visualization with Cytoscape.js.

Scientific Applications:

• Study of Cellular Processes: Enables holistic analysis of molecular interactions in Homo sapiens to investigate cellular processes in health and disease.
• Drug Discovery: Supports analysis of drug-target interactions to inform drug discovery and pharmacological studies.
• Pathway Elucidation and Metabolic Network Studies: Integrates pathway and metabolic data to facilitate pathway elucidation and metabolic network investigations.
• Functional Genomics: Enables gene set analyses linked to protein complexes for functional genomics research.

Methodology:

Integrates data from 30 distinct databases; applies the IntScore confidence assessment to binary protein interactions; performs pathway analysis for metabolite lists, gene set analysis based on protein complexes, and induced network modules analysis; uses overlap-graph visualization and implements graph rendering with Cytoscape.js.