The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
The BioGRID Interaction Database: 2011 update
Open accessAbstract
The Biological General Repository for Interaction Datasets (BioGRID) is a public database that archives and disseminates genetic and protein interaction data from model organisms and humans (http://www.thebiogrid.org). BioGRID currently holds 347,966 interactions (170,162 genetic, 177,804 protein) curated from both high-throughput data sets and individual focused studies, as derived from over 23,000 publications in the primary literature. Complete coverage of the entire literature is maintained for budding yeast (Saccharomyces cerevisiae), fission yeast (Schizosaccharomyces pombe) and thale cress (Arabidopsis thaliana), and efforts to expand curation across multiple metazoan species are underway. The BioGRID houses 48,831 human protein interactions that have been curated from 10,247 publications. Current curation drives are focused on particular areas of biology to enable insights into conserved networks and pathways that are relevant to human health. The BioGRID 3.0 web interface contains new search and display features that enable rapid queries across multiple data types and sources. An automated Interaction Management System (IMS) is used to prioritize, coordinate and track curation across international sites and projects. BioGRID provides interaction data to several model organism databases, resources such as Entrez-Gene and other interaction meta-databases. The entire BioGRID 3.0 data collection may be downloaded in multiple file formats, including PSI MI XML. Source code for BioGRID 3.0 is freely available without any restrictions.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The Genetic Landscape of a Cell
Costanzo, M., Baryshnikova, A., Bellay, J., Kim, Y., Spear, E. D., Sevier, C. S., Ding, H., Koh, J. L. Y., Toufighi, K., Mostafavi, S., et al. (2010) · Science · doi:10.1126/science.1180823 · Cited by 2,162
Network organization of the human autophagy system
Behrends, C., Sowa, M. E., Gygi, S. P., & Harper, J. W. (2010) · Nature · doi:10.1038/nature09204 · Cited by 1,554
ProHits: integrated software for mass spectrometry–based interaction proteomics
Liu, G., Zhang, J., Larsen, B., Stark, C., Breitkreutz, A., Lin, Z.-Y., Breitkreutz, B.-J., Ding, Y., Colwill, K., Pasculescu, A., et al. (2010) · Nature Biotechnology · doi:10.1038/nbt1010-1015 · Cited by 243
Self-citation
Cited by
STRING v9.1: protein-protein interaction networks, with increased coverage and integration
Franceschini, A., Szklarczyk, D., Frankild, S., Kuhn, M., Simonovic, M., Roth, A., Lin, J., Minguez, P., Bork, P., von Mering, C., et al. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1094 · Cited by 4,398
Uncovering disease-disease relationships through the incomplete interactome
Menche, J., Sharma, A., Kitsak, M., Ghiassian, S. D., Vidal, M., Loscalzo, J., & Barabási, A.-L. (2015) · Science · doi:10.1126/science.1257601 · Cited by 1,546
The BioPlex network: a systematic exploration of the human interactome
Huttlin, E. L., Ting, L., Bruckner, R. J., Gebreab, F., Gygi, M. P., Szpyt, J., Tam, S., Zarraga, G., Colby, G., Baltier, K., et al. (2015) · Cell · doi:10.1016/j.cell.2015.06.043 · Cited by 1,425
“Finally, several databases archive protein interactions from literature (Franceschini et al., 2013; Licata et al., 2012; Ruepp et al., 2010; Stark et al., 2011; Warde-Farley et al., 2010).”
A global genetic interaction network maps a wiring diagram of cellular function
Costanzo, M., VanderSluis, B., Koch, E. N., Baryshnikova, A., Pons, C., Tan, G., Wang, W., Usaj, M., Hanchard, J., Lee, S. D., et al. (2016) · Science · doi:10.1126/science.aaf1420 · Cited by 1,240
Combinatorial drug therapy for cancer in the post-genomic era
Al-Lazikani, B., Banerji, U., & Workman, P. (2012) · Nature Biotechnology · doi:10.1038/nbt.2284 · Cited by 1,070
Network-based in silico drug efficacy screening
Guney, E., Menche, J., Vidal, M., & Barábasi, A.-L. (2016) · Nature Communications · doi:10.1038/ncomms10331 · Cited by 625
Interactome3D: adding structural details to protein networks
Mosca, R., Céol, A., & Aloy, P. (2013) · Nature Methods · doi:10.1038/nmeth.2289 · Cited by 479
Systematic Evaluation of Molecular Networks for Discovery of Disease Genes
Huang, J. K., Carlin, D. E., Yu, M. K., Zhang, W., Kreisberg, J. F., Tamayo, P., & Ideker, T. (2018) · Cell Systems · doi:10.1016/j.cels.2018.03.001 · Cited by 289
PomBase: a comprehensive online resource for fission yeast
Wood, V., Harris, M. A., McDowall, M. D., Rutherford, K., Vaughan, B. W., Staines, D. M., Aslett, M., Lock, A., Bahler, J., Kersey, P. J., et al. (2012) · Nucleic Acids Research · doi:10.1093/nar/gkr853 · Cited by 321
CRISPR/Cas9-based engineering of the epigenome
Pulecio, J., Verma, N., Mejía-Ramírez, E., Huangfu, D., & Raya, A. (2017) · Cell Stem Cell · doi:10.1016/j.stem.2017.09.006 · Cited by 300
Passing Messages between Biological Networks to Refine Predicted Interactions
Glass, K., Huttenhower, C., Quackenbush, J., & Yuan, G.-C. (2013) · PLoS ONE · doi:10.1371/journal.pone.0064832 · Cited by 266
Pavlidis, P., Jensen, J. D., Stephan, W., & Stamatakis, A. (2012) · Molecular Biology and Evolution · doi:10.1093/molbev/mss136 · Cited by 221
Evidence that RNA Viruses Drove Adaptive Introgression between Neanderthals and Modern Humans
Enard, D., & Petrov, D. A. (2018) · Cell · doi:10.1016/j.cell.2018.08.034 · Cited by 208
AutismKB: an evidence-based knowledgebase of autism genetics
Xu, L.-M., Li, J.-R., Huang, Y., Zhao, M., Tang, X., & Wei, L. (2012) · Nucleic Acids Research · doi:10.1093/nar/gkr1145 · Cited by 179
A gene ontology inferred from molecular networks
Dutkowski, J., Kramer, M., Surma, M. A., Balakrishnan, R., Cherry, J. M., Krogan, N. J., & Ideker, T. (2013) · Nature Biotechnology · doi:10.1038/nbt.2463 · Cited by 184
Poultney, C. S., Goldberg, A. P., Drapeau, E., Kou, Y., Harony-Nicolas, H., Kajiwara, Y., De Rubeis, S., Durand, S., Stevens, C., Rehnström, K., et al. (2013) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2013.09.001 · Cited by 169
Kovatcheva, M., Liu, D. D., Dickson, M. A., Klein, M. E., O’Connor, R., Wilder, F. O., Socci, N. D., Tap, W. D., Schwartz, G. K., Singer, S., et al. (2015) · Oncotarget · doi:10.18632/oncotarget.3364 · Cited by 142
Integrated systems analysis reveals a molecular network underlying autism spectrum disorders
Li, J., Shi, M., Ma, Z., Zhao, S., Euskirchen, G., Ziskin, J., Urban, A., Hallmayer, J., & Snyder, M. (2014) · Molecular Systems Biology · doi:10.15252/msb.20145487 · Cited by 132
“We first generated a new topological protein interaction network using the most comprehensive human protein interactome from BioGrid (Stark et al , 2011) comprising 13,039 proteins and 69,113 curated interactions (see Materials and Methods, and Supplementary Dataset S1).”
Scheckel, C., Drapeau, E., Frias, M. A., Park, C. Y., Fak, J., Zucker-Scharff, I., Kou, Y., Haroutunian, V., Ma'ayan, A., Buxbaum, J. D., et al. (2016) · eLife · doi:10.7554/elife.10421 · Cited by 139
Genotype to phenotype via network analysis
Carter, H., Hofree, M., & Ideker, T. (2013) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2013.10.003 · Cited by 132
A genomic toolkit to investigate kinesin and myosin motor function in cells
Maliga, Z., Junqueira, M., Toyoda, Y., Ettinger, A., Mora-Bermúdez, F., Klemm, R. W., Vasilj, A., Guhr, E., Ibarlucea-Benitez, I., Poser, I., et al. (2013) · Nature Cell Biology · doi:10.1038/ncb2689 · Cited by 103
Fungal Hsp90: a biological transistor that tunes cellular outputs to thermal inputs
Leach, M. D., Klipp, E., Cowen, L. E., & Brown, A. J. P. (2012) · Nature Reviews Microbiology · doi:10.1038/nrmicro2875 · Cited by 107
Miteva, Y. V., Budayeva, H. G., & Cristea, I. M. (2013) · Analytical Chemistry · doi:10.1021/ac3033257 · Cited by 105
Mirsynergy: detecting synergistic miRNA regulatory modules by overlapping neighbourhood expansion
Li, Y., Liang, C., Wong, K.-C., Luo, J., & Zhang, Z. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu373 · Cited by 83
Systematic tracking of dysregulated modules identifies novel genes in cancer
Srihari, S., & Ragan, M. A. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt191 · Cited by 77
A survey on literature based discovery approaches in biomedical domain
Gopalakrishnan, V., Jha, K., Jin, W., & Zhang, A. (2019) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2019.103141 · Cited by 76
Noma, A., Yi, S., Katoh, T., Takai, Y., Suzuki, T., & Suzuki, T. (2011) · RNA · doi:10.1261/rna.2653411 · Cited by 71
Stevens, A., Hanson, D., Whatmore, A., Destenaves, B., Chatelain, P., & Clayton, P. (2013) · BMC Genomics · doi:10.1186/1471-2164-14-547 · Cited by 65
Vidal, M., Chan, D. W., Gerstein, M., Mann, M., Omenn, G. S., Tagle, D., Sechi, S., & Participants, W. (2012) · Clinical Proteomics · doi:10.1186/1559-0275-9-6 · Cited by 41
Gingras, A.-C., & Raught, B. (2012) · FEBS Letters · doi:10.1016/j.febslet.2012.03.065 · Cited by 34
Presence and utility of intrinsically disordered regions in kinases
Kathiriya, J. J., Pathak, R. R., Clayman, E., Xue, B., Uversky, V. N., & Davé, V. (2014) · Molecular BioSystems · doi:10.1039/c4mb00224e · Cited by 30
A Network Approach to Wound Healing
Arodz, T., Bonchev, D., & Diegelmann, R. F. (2013) · Advances in Wound Care · doi:10.1089/wound.2012.0386 · Cited by 22
Duan, D., Hanson, M., Holland, D. O., & Johnson, M. E. (2022) · Scientific Reports · doi:10.1038/s41598-022-09259-w · Cited by 15
Metadata
- Authors
- Stark, C., Breitkreutz, B.-J., Chatr-aryamontri, A., Boucher, L., Oughtred, R., Livstone, M. S., Nixon, J., Van Auken, K., Wang, X., Shi, X., Reguly, T., Rust, J. M., Winter, A., Dolinski, K., & Tyers, M.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2010-11-11
- Volume
- 39
- Issue
- Database
- Pages
- D698-D704
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- OpenAlex
- W2915108429
- Cited by
- 854
- References
- 3
- FWCI
- 55.41
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.