Expressed phenotypes may arise due to interactions between multiple genes in a system and effects from the surrounding environment.  Therefore, a high systems-level view is needed to identify gene sets causal for a trait.  The ability to predict genes that effect important traits is of great importance to agriculture and health.   Systems genetic approaches, that combine genomics, gene co-expression networks and data from genetic studies help provide a view at the systems-level of gene interactions.  Because co-expressed genes tend to be involved in similar processes, it is expected that co-expressed genes may work together to give rise to specific pheontypes.  

The network module serves as the basic unit of exploration in this site. 


GeneNet Engine is provided by the Feltus Lab at Clemson University in cooperation with the Ficklin Lab at Washington State University. .  This database is an exploratory tool to aid hypothesis and biomarker development at a systems-level for genotype-phenotype relationships.

How to Cite

If you find the data useful in your published work please cite this site using the following citations:

Ficklin SP, Feltus FA. A systems-genetics approach and data mining tool to assist in the discovery of genes underlying complex traits in Oryza sativa . PloS one. 2013; 8(7):e68551..