genenetwork

A gene network, sometimes written as genenetwork, is a representation of functional relationships among genes and their products. In systems biology, networks are used to model how genes regulate each other, participate in signaling pathways, or interact within molecular complexes. Networks can be constructed at multiple scales, from small circuits to genome-wide maps, and they can describe regulatory, physical, or genetic interactions.

Common types include gene regulatory networks (GRNs), which describe directional regulatory interactions such as transcriptional activation or repression; gene co-expression networks, where edges indicate correlated expression patterns across samples; genetic interaction networks, which reflect how combinations of perturbations affect phenotypes; protein–protein interaction networks; and metabolic networks that connect enzymes to metabolic steps.

Construction and data sources: Networks are inferred or curated from experimental data and literature. Co-expression networks use statistical associations or mutual information; GRNs often employ Bayesian networks or machine learning to infer directionality; integration of transcriptomic, proteomic, genetic perturbation, and literature-derived data improves reliability. Edges may be weighted to reflect confidence and may be directed to reflect regulatory influence.

Applications: Gene networks are used to identify functional modules, reveal regulatory programs underlying development or disease, prioritize candidate genes for further study, and inform drug target discovery and precision medicine.

Limitations: Inference remains challenging due to context specificity, dynamic changes over time, and data noise. Edges can represent indirect associations, and validation experiments are typically required. Large networks also pose computational and interpretive challenges.

See also: Systems biology; network biology; Cytoscape; WGCNA.