| Summary: | High-throughput experimental technologies gradually shift the paradigm of
biological research from hypothesis-validation toward hypothesis-generation
science. Translating diverse types of large-scale experimental data into
testable hypotheses, however, remains a daunting task. We previously
demonstrated that heterogeneous genomics data can be integrated into a single
genome-scale gene network with high prediction power for ribonucleic acid
interference (RNAi) phenotypes in Caenorhabditis elegans, a
popular metazoan model in the study of developmental biology, neurobiology and
genetics. Here, we present WormNet version 3 (v3), which is a new
network-assisted hypothesis-generating server for C. elegans.
WormNet v3 includes major updates to the base gene network, which substantially
improved predictions of RNAi phenotypes. The server generates various gene
network-based hypotheses using three complementary network methods: (i) a
phenotype-centric approach to ‘find new members for a pathway’;
(ii) a gene-centric approach to ‘infer functions from network
neighbors’ and (iii) a context-centric approach to ‘find
context-associated hub genes’, which is a new method to identify key
genes that mediate physiology within a specific context. For example, we
demonstrated that the context-centric approach can be used to identify potential
molecular targets of toxic chemicals. WormNet v3 is freely accessible at
http://www.inetbio.org/wormnet.
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