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. 2010 Jul;38(Web Server issue):W214-20.
doi: 10.1093/nar/gkq537.

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

David Warde-Farley  1 , Sylva L Donaldson, Ovi Comes, Khalid Zuberi, Rashad Badrawi, Pauline Chao, Max Franz, Chris Grouios, Farzana Kazi, Christian Tannus Lopes, Anson Maitland, Sara Mostafavi, Jason Montojo, Quentin Shao, George Wright, Gary D Bader, Quaid Morris
Affiliations

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

David Warde-Farley et al. Nucleic Acids Res. 2010 Jul.

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.

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Figures

Figure 1.
Figure 1.
Images from http://www.genemania.org. (A) The initial query screen, with the advanced options panel expanded, providing the user the ability to select desired networks, choose a network weighting method and the number of genes to return. (B) The results page for the mouse default query, which is a set of genes involved in leukemia. Users can examine information associated with each gene and network by expanding their entries on the corresponding panel. We include linkouts to model organism databases (FlyBase, WormBase, SGD and TAIR) and to the Arabidopsis resource BAR (19) that is useful to plant users.
Figure 2.
Figure 2.
Effects of data set selection on network topology. GeneMANIA showing the results of two yeast queries. (A) The yeast cell-cycle default query, using all default parameters. (B) The yeast cell-cycle default query, using default network weighting method. Only shared protein domain data sets are selected.
Figure 3.
Figure 3.
Effects of network weighting method selection on network topology. GeneMANIA showing the results of two human queries. (A) The human DNA repair and replication default query, using all default parameters. (B) The human DNA repair and replication default query, using the default data set selection but with the ‘Equal by data type’ network weighing method selected. Some genes and interactions found in this query that were not present in the default query (shown in A) are indicated by arrows.
See this image and copyright information in PMC

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