ePath

ePath predicts essential genes in prokaryotic species by combining KEGG Ortholog (KO) annotations with experimental essentiality data and functional scoring to prioritize essential KOs for functional and therapeutic studies.

Key Features:

• Extensive database access: Provides essential gene (EG) prediction results for over 4,000 prokaryotic species.
• Integration with KEGG Orthologs (KO): Links gene essentiality predictions to KO-based functional annotations.
• E_score: Reflects the presence and essentiality of a given KO in existing experimental datasets on gene essentiality.
• P_score: Assesses gene essentiality based on involvement in biological processes such as genetic information processing, cell envelope maintenance, and energy production.
• Prediction accuracy: Validation studies report success rates ranging from 75% to 91%.

Scientific Applications:

• Functional Genomics: Annotating and prioritizing essential genes to elucidate gene function within microbial genomes.
• Metabolic Engineering: Identifying essential gene targets for modification to alter or optimize metabolic pathways.
• Antibiotic Development: Discovering essential genes that serve as potential targets for new antimicrobial agents.

Methodology:

Computationally combines experimental-data-derived E_score with function-based P_score together with KEGG Ortholog annotations to generate essential gene predictions.