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GeneMANIA update 2018

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Franz, Max, Rodriguez, Harold, Lopes, Christian, Zuberi, Khalid, Montojo, Jason, Bader, Gary D, Morris, Quaid·2018·Nucleic Acids Research
DOI 10.1093/nar/gky311PMC PMC6030815
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Abstract

GeneMANIA (http://genemania.org) is a flexible user-friendly web site for generating hypotheses about gene function, analyzing gene lists and prioritizing genes for functional assays. Given a query gene list, GeneMANIA finds functionally similar genes using a wealth of genomics and proteomics data. In this mode, it weights each functional genomic dataset according to its predictive value for the query. Another use of GeneMANIA is gene function prediction. Given a single query gene, GeneMANIA finds genes likely to share function with it based on their interactions with it. Enriched Gene Ontology categories among this set can point to the function of the gene. Nine organisms are currently supported (Arabidopsis thaliana, Caenorhabditis elegans, Danio rerio, Drosophila melanogaster, Escherichia coli, Homo sapiens, Mus musculus, Rattus norvegicus and Saccharomyces cerevisiae). Hundreds of data sets and hundreds of millions of interactions have been collected from GEO, BioGRID, IRefIndex and I2D, as well as organism-specific functional genomics data sets. Users can customize their search by selecting specific data sets to query and by uploading their own data sets to analyze. We have recently updated the user interface to GeneMANIA to make it more intuitive and make more efficient use of visual space. GeneMANIA can now be used effectively on a variety of devices.

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  • The causal gene, CNP, for the second-ranked disease, hypomyelinating leukodystropy-20, is three hops away from ATP5PO in the physical protein interaction network.

    “The causal gene, CNP, for the second-ranked disease, hypomyelinating leukodystropy-20 (MIM:619071), is three hops away from ATP5PO in the physical protein interaction network67,68”

    From Few shot learning for phenotype-driven diagnosis of patients with rare genetic diseases (2025) · cites this paper as [68]

    The Introduction’s Use cases section (page unavailable) says GeneMANIA can search selected networks and display connections among query genes, including physical interactions. It does not report that CNP is three hops from ATP5PO or identify CNP as the causal gene for the named disease; searches for those gene names and the three-hop claim found no such passage. (LLM, conf=0.82)

    Experimental — accuracy not yet measured

  • KRT19 and STAT5B associations with GDF-15 were supported by GeneMANIA as well as STRING database.

    “KRT19 and STAT5B associations with GDF-15 were supported by GeneMANIA as well as STRING database.”

    From Genetic determinants of plasma protein levels in the Estonian population (2024) · cites this paper as [39]

    The Introduction’s “Use cases” section describes GeneMANIA as a tool for finding connected genes, so the paper supports identifying GeneMANIA as the tool used. It does not report that KRT19 or STAT5B is associated with GDF-15; searches for those genes and STRING found no such result in our copy. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

  • At the low confidence interaction score of 0.15, TMEM119 and SELPLG have a shared connection due to co-expression and co-mentioning in PubMed abstracts, and the functional link was also supported by GeneMANIA.

    “However, at the low confidence interaction score of 0.15, TMEM119 and SELPLG have a shared connection due to co-expression and co-mentioning in PubMed abstracts, functional link was also supported by GeneMANIA.”

    From Genetic determinants of plasma protein levels in the Estonian population (2024) · cites this paper as [39]

    The Introduction (Use cases; page unavailable) says GeneMANIA returns connections among query genes and can help generate hypotheses about gene function. It does not report a TMEM119–SELPLG connection, an interaction score of 0.15, or co-expression and co-mentioning in PubMed abstracts; searches for the gene names and score found no such passage. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

  • Ten of the identified genes harbouring rare SNPs (CKAP5, GDF15, JAKMIP1, KRT19, STAT5B, SLC35E1, RNF112, TUBGCP4, ZNF766 and PPAPDC1B), including the gene encoding the identified pQTL protein, formed a shared network with GDF-15 based on co-expression (57.85%), pathway (19.97%), physical (18.45%) and genetic (3.73%) interactions, according to GeneMANIA.

    “Ten of the identified genes harbouring rare SNPs (CKAP5, GDF15, JAKMIP1, KRT19, STAT5B, SLC35E1, RNF112, TUBGCP4, ZNF766 and PPAPDC1B), including gene encoding identified pQTL protein, formed shared network with GDF-15, based on co-expression (57.85%), pathway (19.97%), physical (18.45%) and genetic (3.73%) interactions, according to GeneMANIA.”

    From Genetic determinants of plasma protein levels in the Estonian population (2024) · cites this paper as [39]

    Split into 2 atoms — 0 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 1 unverifiable. Expand the claim to see per-atom verdicts.

    Experimental — accuracy not yet measured

  • A follow-up GeneMANIA network analysis revealed a shared network based on physical interactions (77.64%), co-expression (8.01%), predicted functional relationship between genes (5.37%), co-localisation (3.63%), genetic interactions (2.87%), pathway (1.88%) and shared protein domains (0.60%).

    “a follow-up GeneMANIA network analysis39,40 revealed a shared network based on physical interactions (77.64%), co-expression (8.01%), predicted functional relationship between genes (5.37%), co-localisation (3.63%), genetic interactions (2.87%), pathway (1.88%) and shared protein domains (0.60%).”

    From Genetic determinants of plasma protein levels in the Estonian population (2024) · cites this paper as [39]

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References 15 · Cited by 1,413

Research works printed but not linked: 13

  1. [1]Warde-Farley D., Donaldson S.L., Comes O., Zuberi K., Badrawi R., Chao P., Franz M., Grouios C., Kazi F., Lopes C.T. The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function. Nucleic Acids Res. 2010; 38: W214– W220. 20576703 PMC2896186
  2. [3]Mostafavi S., Ray D., Warde-Farley D., Grouios C., Morris Q. GeneMANIA: a real-time multiple association network integration algorithm for predicting gene function. Genome Biol. 2008; 9: S4. PMC2447538 18613948
  3. [4]Mostafavi S., Goldenberg A., Morris Q. Predicting node characteristics from molecular networks. Network Biol.: Methods Applic. 2011; 781: 399– 414. 21877293
  4. [5]Mostafavi S., Morris Q. Combining many interaction networks to predict gene function and analyze gene lists. Proteomics. 2012; 12: 1687– 1696. 22589215
  5. [6]Mostafavi S., Morris Q. Fast integration of heterogeneous data sources for predicting gene function with limited annotation. Bioinformatics. 2010; 26: 1759– 1765. 20507895 PMC2894508
  6. [7]Montojo J., Zuberi K., Rodriguez H., Kazi F., Wright G., Donaldson S.L., Morris Q., Bader G.D. GeneMANIA Cytoscape plugin: fast gene function predictions on the desktop. Bioinformatics. 2010; 26: 2927– 2928. 20926419 PMC2971582
  7. [8]Myers C.L., Robson D., Wible A., Hibbs M.A., Chiriac C., Theesfeld C.L., Dolinski K., Troyanskaya O.G. Discovery of biological networks from diverse functional genomic data. Genome Biol. 2005; 6: R114. 16420673 PMC1414113
  8. [9]Kotlyar M., Pastrello C., Sheahan N., Jurisica I. Integrated interactions database: tissue-specific view of the human and model organism interactomes. Nucleic Acids Res. 2015; 44: D536– D541. 26516188 PMC4702811
  9. [10]Musso G., Tasan M., Mosimann C., Beaver J.E., Plovie E., Carr L.A., Chua H.N., Dunham J., Zuberi K., Rodriguez H. Novel cardiovascular gene functions revealed via systematic phenotype prediction in zebrafish. Development. 2014; 141: 224– 235. 24346703 PMC3865760
  10. [11]Vlasblom J., Zuberi K., Rodriguez H., Arnold R., Gagarinova A., Deineko V., Kumar A., Leung E., Rizzolo K., Samanfar B. Novel function discovery with GeneMANIA: a new integrated resource for gene function prediction in Escherichia coli. Bioinformatics. 2014; 31: 306– 310. 25316676 PMC4308668
  11. [12]Gough J., Karplus K., Hughey R., Chothia C. Assignment of homology to genome sequences using a library of hidden Markov models that represent all proteins of known structure. J. Mol. Biol. 2001; 313: 903– 919. 11697912
  12. [14]Franz M., Lopes C.T., Huck G., Dong Y., Sumer O., Bader G.D. Cytoscape. js: a graph theory library for visualisation and analysis. Bioinformatics. 2015; 32: 309– 311. 26415722 PMC4708103
  13. [15]Dogrusoz U., Giral E., Cetintas A., Civril A., Demir E. A layout algorithm for undirected compound graphs. Inform. Sci. 2009; 179: 980– 994.

Authors
Franz, M., Rodriguez, H., Lopes, C., Zuberi, K., Montojo, J., Bader, G. D., & Morris, Q.
Affiliations
University of Toronto (CA)
Corresponding author
  • Bader, Gary D
  • Morris, Quaid
ORCID
Venue
Nucleic Acids Research
Publisher
Oxford University Press (OUP)
Published
2018-06-15
Volume
46
Issue
W1
Pages
W60-W64
ISSN
  • 0305-1048 (ISSN-L)
  • 1362-4962
DOI
10.1093/nar/gky311
PMC
PMC6030815
OpenAlex
W2809000676
Cited by
1,413
References
15
Citations by year
2026: 185 · 2025: 280 · 2024: 297 · 2023: 230 · 2022: 147 · 2021: 160 · 2020: 74 · 2019: 38 · 2018: 2
FWCI
24.64
Type
journal article
Language
en
Open access
Licence
Locations
  • Nucleic Acids Research (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Funders
National Institutes of Health (P41 GM103504, R01 GM070743, U41 HG006623)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Biomedical Text Mining and Ontologies
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
Keywords
GeneMANIA, gene function prediction, gene interaction networks, functional genomic data, gene ontology enrichment, web application, user interface redesign
MeSH terms
Algorithms, Animals, Drosophila melanogaster, Humans, Saccharomyces cerevisiae, Software, Zebrafish, Arabidopsis, Internet, Genomics, Databases, Genetic, Mice, Rats, Gene Regulatory Networks, Gene Ontology

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