a probabilistic functional gene network of protein-encoding genes of Caenorhabditis elegans, constructed using a modified Bayesian integration of many different data types from several different organisms, with each data type weighted according to how well it links genes that are known to function together in C. elegans. Each interaction in WormNet has an associated log-likelihood score (LLS) that measures the probability of an interaction representing a true functional linkage between two genes.
by collaboration among Lee Lab at Yonsei University, Korea, Marcotte Lab at University of Texas at Austin, USA, Fraser Lab at University of Toronto, Canada and Lehner Lab at EMBL-CRG Systems Biology Research Unit, Barcelona, Spain.
please go to the search page and enter a gene, or list of genes, in the box provided, using Wormbase public or sequence gene names (e.g. dys-1 or F15D3.1). The search will return all of the genes that are directly connected to an input gene (or set of genes), ranked according to their log-likelihood scores. The evidence for each interaction is indicated using the evidence codes listed at the bottom of each page. WormNet is built on Wormbase release WB170 gene identifiers.
Current network statistics :
click to search with the former version, WormNet v.1.
A single network comprising the majority of genes accurately predicts the phenotypic effects of gene perturbation in C. elegans
Insuk Lee, Ben Lehner, Catriona Crombie, Wendy Wang, Andrew G. Fraser, and Edward M. Marcotte
Nature Genetics, Vol 40, pp181-188 (2008)
Predicting genetic modifier loci using functional gene networks
Insuk Lee, Ben Lehner, Tanya Vavouri, Junha Shin, Andrew G. Fraser, and Edward M. Marcotte
Genome Research, 20(8), pp1143-1153 (2010)