IIS

IIS integrates protein, metabolite, gene, and drug data to construct annotated interactome networks for systems biology analyses, including protein/gene function inference, assessment of cellular metabolic variation, and therapeutic target validation from high-throughput physical, genetic, and chemical-genetic interaction data.

Key Features:

• Submission Module: Accepts raw experimental data inputs, including Sanger sequencing reads from two-hybrid systems.
• Search Module: Processes reads and assembles them into contigs and singlets and indexes proteins, genes, metabolites, and drugs for downstream analysis.
• Annotation Module: Assigns annotations from multiple databases to contigs/singlets and entity lists, generates annotation tables, and supports manual curation.
• Interactome Module: Maps annotated entities to an integrated database and constructs networks incorporating protein and metabolite expression/concentration levels, subcellular localization, and computed topological metrics.
• Functional Enrichment and Export: Performs Gene Ontology (GO) biological process and KEGG pathway enrichment and exports networks in XGMML format compatible with Cytoscape.
• Interaction Integration: Integrates physical, genetic, and chemical-genetic interactions and accommodates high-throughput datasets such as yeast two-hybrid, proteomics, and metabolomics.

Scientific Applications:

• Protein/Gene Function Inference: Use annotated interactome networks and topology to infer protein and gene functions.
• Cellular Metabolic Variation Analysis: Assess metabolic changes by mapping metabolite concentration/expression and KEGG pathway enrichment.
• Therapeutic Target Validation: Integrate drug data with chemical-genetic interactions to support validation of therapeutic targets.
• Network Topology and Localization Studies: Analyze computed topological metrics and subcellular localization to interpret network organization and dynamics.
• Integration of High-Throughput Interaction Data: Consolidate yeast two-hybrid, proteomics, and metabolomics datasets for systems biology investigations.

Methodology:

Accept raw reads (e.g., Sanger two-hybrid), assemble reads into contigs/singlets, assign annotations from multiple databases and generate annotation tables, map annotations to an integrated database to construct networks with expression/concentration levels and subcellular localization, compute topological metrics, perform GO and KEGG enrichment, and export networks as XGMML for Cytoscape.