WormNet v3

WormNet v3 predicts RNAi phenotypes and generates gene-function hypotheses for Caenorhabditis elegans by integrating diverse genomics data into a genome-scale gene network.

Key Features:

• Genome-scale gene network: Integrates heterogeneous genomics data into a unified network covering the C. elegans genome.
• RNAi phenotype prediction: Improves prediction accuracy for RNAi phenotypes using updated network information.
• Phenotype-centric approach: Identifies new members of existing pathways to expand known phenotype-associated gene sets.
• Gene-centric approach: Infers gene functions from network neighbors based on interaction patterns.
• Context-centric approach: Identifies context-associated hub genes that mediate physiological responses in specific contexts such as exposure to toxic chemicals.
• Hypothesis generation: Produces testable molecular hypotheses from integrated network analyses.

Scientific Applications:

• Developmental biology: Facilitates discovery of genes and pathways underlying developmental processes in C. elegans.
• Neurobiology: Supports identification of genes and network modules involved in neural function and behavior.
• Genetics and functional genomics: Aids prioritization of candidate genes and molecular targets for experimental validation using RNAi and other assays.

Methodology:

Constructs a genome-scale gene network by integrating diverse genomics datasets and applies three network methods (phenotype-centric, gene-centric, context-centric) to predict RNAi phenotypes, infer gene functions from network neighbors, and identify context-associated hub genes.