GeneFAS

GeneFAS predicts gene functions by integrating protein-protein interactions, protein complexes, microarray gene expression profiles, and protein annotations to infer cellular functions.

Key Features:

• Data integration: Combines protein-protein interactions, protein complexes, microarray gene expression profiles, and annotations of known proteins to provide multi-evidence support for function inference.
• Organism-specific data integration: Supports organism-specific workspaces for incorporating experimental datasets and annotation information relevant to a chosen organism.
• Biological discovery and hypothesis generation: Integrates diverse datasets to enable exploration of gene roles, interactions, and generation of testable hypotheses about cellular functions.
• Testing and training capabilities: Includes functionalities for testing and training predictive models using supplied datasets and annotations.

Scientific Applications:

• Functional genomics: Prioritizes and annotates genes for experimental characterization and functional studies.
• Systems biology: Elucidates gene roles and interaction networks to support systems-level analyses of cellular processes.
• Personalized medicine: Links gene function predictions to cellular mechanisms relevant for personalized medicine investigations.
• Hypothesis generation: Facilitates generation of hypotheses about gene function and interactions across integrated data types.

Methodology:

Integrates protein-protein interactions, protein complex data, microarray gene expression profiles, and protein annotations and correlates PPI with expression profiles and known annotations to predict cellular functions; includes testing and training of predictive models.