The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function

D Warde-Farley, SL Donaldson, O Comes… - Nucleic acids …, 2010 - academic.oup.com
D Warde-Farley, SL Donaldson, O Comes, K Zuberi, R Badrawi, P Chao, M Franz, C Grouios…
Nucleic acids research, 2010academic.oup.com
Abstract GeneMANIA (http://www. genemania. org) is a flexible, user-friendly web interface
for generating hypotheses about gene function, analyzing gene lists and prioritizing genes
for functional assays. Given a query list, GeneMANIA extends the list with functionally similar
genes that it identifies using available genomics and proteomics data. GeneMANIA also
reports weights that indicate the predictive value of each selected data set for the query. Six
organisms are currently supported (Arabidopsis thaliana, Caenorhabditis elegans …
Abstract
GeneMANIA (http://www.genemania.org) is a flexible, user-friendly web interface for generating hypotheses about gene function, analyzing gene lists and prioritizing genes for functional assays. Given a query list, GeneMANIA extends the list with functionally similar genes that it identifies using available genomics and proteomics data. GeneMANIA also reports weights that indicate the predictive value of each selected data set for the query. Six organisms are currently supported (Arabidopsis thaliana, Caenorhabditis elegans, Drosophila melanogaster, Mus musculus, Homo sapiens and Saccharomyces cerevisiae) and hundreds of data sets have been collected from GEO, BioGRID, Pathway Commons and I2D, as well as organism-specific functional genomics data sets. Users can select arbitrary subsets of the data sets associated with an organism to perform their analyses and can upload their own data sets to analyze. The GeneMANIA algorithm performs as well or better than other gene function prediction methods on yeast and mouse benchmarks. The high accuracy of the GeneMANIA prediction algorithm, an intuitive user interface and large database make GeneMANIA a useful tool for any biologist.
Oxford University Press