The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
DAVID: a web server for functional enrichment analysis and functional annotation of gene lists (2021 update)
Open accessAbstract
DAVID is a popular bioinformatics resource system including a web server and web service for functional annotation and enrichment analyses of gene lists. It consists of a comprehensive knowledgebase and a set of functional analysis tools. Here, we report all updates made in 2021. The DAVID Gene system was rebuilt to gain coverage of more organisms, which increased the taxonomy coverage from 17 399 to 55 464. All existing annotation types have been updated, if available, based on the new DAVID Gene system. Compared with the last version, the number of gene-term records for most annotation types within the updated Knowledgebase have significantly increased. Moreover, we have incorporated new annotations in the Knowledgebase including small molecule-gene interactions from PubChem, drug-gene interactions from DrugBank, tissue expression information from the Human Protein Atlas, disease information from DisGeNET, and pathways from WikiPathways and PathBank. Eight of ten subgroups split from Uniprot Keyword annotation were assigned to specific types. Finally, we added a species parameter for uploading a list of gene symbols to minimize the ambiguity between species, which increases the efficiency of the list upload and eliminates confusion for users. These current updates have significantly expanded the Knowledgebase and enhanced the discovery power of DAVID.
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 sequence of the human genome
Venter, J. C., Adams, M. D., Myers, E. W., Li, P. W., Mural, R. J., Sutton, G. G., Smith, H. O., Yandell, M., Evans, C. A., Holt, R. A., et al. (2001) · Science · doi:10.1126/science.1058040 · Cited by 13,909
DAVID: Database for Annotation, Visualization, and Integrated Discovery
Dennis, G., Sherman, B. T., Hosack, D. A., Yang, J., Gao, W., Lane, H. C., & Lempicki, R. A. (2003) · Genome Biology · doi:10.1186/gb-2003-4-5-p3 · Cited by 9,327
Self-citationDrugBank 5.0: a major update to the DrugBank database for 2018
Wishart, D. S., Feunang, Y. D., Guo, A. C., Lo, E. J., Marcu, A., Grant, J. R., Sajed, T., Johnson, D., Li, C., Sayeeda, Z., et al. (2018) · Nucleic Acids Research · doi:10.1093/nar/gkx1037 · Cited by 8,404
An atlas of the protein-coding genes in the human, pig, and mouse brain
Sjöstedt, E., Zhong, W., Fagerberg, L., Karlsson, M., Mitsios, N., Adori, C., Oksvold, P., Edfors, F., Limiszewska, A., Hikmet, F., et al. (2020) · Science · doi:10.1126/science.aay5947 · Cited by 1,151
WikiPathways: Pathway Editing for the People
Pico, A. R., Kelder, T., van Iersel, M. P., Hanspers, K., Conklin, B. R., & Evelo, C. (2008) · PLoS Biology · doi:10.1371/journal.pbio.0060184 · Cited by 701
Cited by
Kolberg, L., Raudvere, U., Kuzmin, I., Adler, P., Vilo, J., & Peterson, H. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad347 · Cited by 1,673
Győrffy, B. (2024) · British Journal of Pharmacology · doi:10.1111/bph.16257 · Cited by 361
From Omics to Multi-Omics: A Review of Advantages and Tradeoffs
Hayes, C. N., Nakahara, H., Ono, A., Tsuge, M., & Oka, S. (2024) · Genes · doi:10.3390/genes15121551 · Cited by 119
Choi, Y.-M., Lee, H., Ann, M., Song, M., Rheey, J., & Jang, J. (2023) · Biofabrication · doi:10.1088/1758-5090/acd95f · Cited by 94
In vitro reconstitution of epigenetic reprogramming in the human germ line
Murase, Y., Yokogawa, R., Yabuta, Y., Nagano, M., Katou, Y., Mizuyama, M., Kitamura, A., Puangsricharoen, P., Yamashiro, C., Hu, B., et al. (2024) · Nature · doi:10.1038/s41586-024-07526-6 · Cited by 80
Macrophages recycle phagocytosed bacteria to fuel immunometabolic responses
Lesbats, J., Brillac, A., Reisz, J. A., Mukherjee, P., Lhuissier, C., Fernández-Monreal, M., Dupuy, J.-W., Sequeira, A., Tioli, G., De La Calle Arregui, C., et al. (2025) · Nature · doi:10.1038/s41586-025-08629-4 · Cited by 74
Adaptive evolution of the enigmatic Takakia now facing climate change in Tibet
Hu, R., Li, X., Hu, Y., Zhang, R., Lv, Q., Zhang, M., Sheng, X., Zhao, F., Chen, Z., Ding, Y., et al. (2023) · Cell · doi:10.1016/j.cell.2023.07.003 · Cited by 55
An integrated multi-omics analysis reveals osteokines involved in global regulation
Liang, W., Wei, T., Hu, L., Chen, M., Tong, L., Zhou, W., Duan, X., Zhao, X., Zhou, W., Jiang, Q., et al. (2024) · Cell Metabolism · doi:10.1016/j.cmet.2024.03.006 · Cited by 67
Integrated analysis of the complete sequence of a macaque genome
Zhang, S., Xu, N., Fu, L., Yang, X., Ma, K., Li, Y., Yang, Z., Li, Z., Feng, Y., Jiang, X., et al. (2025) · Nature · doi:10.1038/s41586-025-08596-w · Cited by 48
Rebak, A. S., Hendriks, I. A., Elsborg, J. D., Buch-Larsen, S. C., Nielsen, C. H., Terslev, L., Kirsch, R., Damgaard, D., Doncheva, N. T., Lennartsson, C., et al. (2024) · Nature Structural & Molecular Biology · doi:10.1038/s41594-024-01214-9 · Cited by 45
microRNA-132 regulates gene expression programs involved in microglial homeostasis
Walgrave, H., Penning, A., Tosoni, G., Snoeck, S., Davie, K., Davis, E., Wolfs, L., Sierksma, A., Mars, M., Bu, T., et al. (2023) · iScience · doi:10.1016/j.isci.2023.106829 · Cited by 41
Haematopoietic stem and progenitor cell heterogeneity is inherited from the embryonic endothelium
Ghersi, J. J., Baldissera, G., Hintzen, J., Luff, S. A., Cheng, S., Xia, I. F., Sturgeon, C. M., & Nicoli, S. (2023) · Nature Cell Biology · doi:10.1038/s41556-023-01187-9 · Cited by 32
Merrill, N. J., Davidson, W. S., He, Y., Díaz Ludovico, I., Sarkar, S., Berger, M. R., McDermott, J. E., Van Eldik, L. J., Wilcock, D. M., Monroe, M. E., et al. (2023) · Science Advances · doi:10.1126/sciadv.adi5571 · Cited by 27
Defining the Parameters for Sorting of RNA Cargo Into Extracellular Vesicles
Abdelgawad, A., Huang, Y., Gololobova, O., Yu, Y., Witwer, K. W., Parashar, V., & Batish, M. (2025) · Journal of Extracellular Vesicles · doi:10.1002/jev2.70113 · Cited by 26
Ciuba, K., Piotrowska, A., Chaudhury, D., Dehingia, B., Duński, E., Behr, R., Soroczyńska, K., Czystowska-Kuźmicz, M., Abbas, M., Bulanda, E., et al. (2025) · Cell Stem Cell · doi:10.1016/j.stem.2024.12.011 · Cited by 25
Jiang, J., Chen, S., Tsou, T., McGinnis, C. S., Khazaei, T., Zhu, Q., Park, J. H., Strazhnik, I.-M., Vielmetter, J., Gong, Y., et al. (2023) · doi:10.1101/2023.04.19.537364 · Cited by 21
Dijkstra, J. J., Neikes, H. K., Rezaeifard, S., Ma, X., Voest, E. E., Tauriello, D. V. F., & Vermeulen, M. (2023) · Journal of Proteome Research · doi:10.1021/acs.jproteome.2c00551 · Cited by 23
PLCG2 modulates TREM2 expression and signaling in response to Alzheimer's disease pathology
Messenger, E. J., Baar, S. A., Bedford, L. M., Tsai, A. P., Lin, P. B., Ferguson, C. A., Xu, G., Wallace, A., Landreth, G. E., Lamb, B. T., et al. (2025) · Alzheimer's & Dementia · doi:10.1002/alz.70231 · Cited by 16
“Enrichment analysis of the DEGs were conducted using DAVID 53,54 and enrichments were considered to be significant if adjusted p value ≤ 0.05.”
InfluentialZhao, W., Yuan, W., Dong, T., Qi, W., Feng, Z., Li, C., & Sun, Y. (2025) · Communications Biology · doi:10.1038/s42003-025-08160-2 · Cited by 16
Rao, A., Lyu, B., Jahan, I., Lubertozzi, A., Zhou, G., Tedeschi, F., Jankowsky, E., Kang, J., Carstens, B., Poss, K. D., et al. (2023) · Development · doi:10.1242/dev.201376 · Cited by 13
Pallante, L., Cannariato, M., Androutsos, L., Zizzi, E. A., Bompotas, A., Hada, X., Grasso, G., Kalogeras, A., Mavroudi, S., Di Benedetto, G., et al. (2024) · Scientific Reports · doi:10.1038/s41598-024-56893-7 · Cited by 12
Wnt/Wingless signaling promotes lipid mobilization through signal-induced transcriptional repression
Liu, M., Hemba-Waduge, R.-U.-S., Li, X., Huang, X., Liu, T.-H., Han, X., Wang, Y., & Ji, J.-Y. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2322066121 · Cited by 12
SHIFTR enables the unbiased identification of proteins bound to specific RNA regions in live cells
Aydin, J., Gabel, A., Zielinski, S., Ganskih, S., Schmidt, N., Hartigan, C. R., Schenone, M., Carr, S. A., & Munschauer, M. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkae038 · Cited by 12
Non-Canonical TERT Activity Initiates Osteogenesis in Calcific Aortic Valve Disease
Cuevas, R. A., Hortells, L., Chu, C. C., Wong, R., Crane, A., Boufford, C. K., Regan, C., Moorhead, W. J., Bashline, M. J., Parwal, A., et al. (2025) · Circulation Research · doi:10.1161/circresaha.122.321889 · Cited by 11
Plant Defence Induction by Meyerozyma guilliermondii in Vitis vinifera L.
Alonso de Robador, J. M., Ortega Pérez, N., Sanchez-Ballesta, M. T., Tello Mariscal, M. L., Pintos López, B., & Gómez-Garay, A. (2023) · Agronomy · doi:10.3390/agronomy13112780 · Cited by 9
Cristiani, A., Dutta, A., Poveda‐Cuevas, S. A., Kern, A., & Bhaskara, R. M. (2024) · Journal of Cellular Biochemistry · doi:10.1002/jcb.30405 · Cited by 9
Heat shock induces silent ribosomes and reorganizes mRNA turnover
Rahaman, S., Schiffelholz, N., Mittal, N., Fröhlich, K. E., Zavolan, M., & Becskei, A. (2025) · Cell Reports · doi:10.1016/j.celrep.2025.116447 · Cited by 9
Bedford, L. M., Tutrow, K. D., Hooper, K., Messenger, E. J., Hernandez, M., Lamb, B. T., Meyer, J. S., Richardson, T. I., & Bissel, S. J. (2025) · Alzheimer's & Dementia · doi:10.1002/alz.70772 · Cited by 8
Strickland, M. R., Wang, Z., Golden, L. R., Wang, H., Lu, P., Ren, Y., Tabor, G. T., Zhao, N., Ulrich, J. D., Han, X., et al. (2026) · Journal of Lipid Research · doi:10.1016/j.jlr.2026.101000 · Cited by 8
Human cellular model systems of β-thalassemia enable in-depth analysis of disease phenotype
Daniels, D. E., Ferrer-Vicens, I., Hawksworth, J., Andrienko, T. N., Finnie, E. M., Bretherton, N. S., Ferguson, D. C. J., Oliveira, A. S. F., Szeto, J.-Y. A., Wilson, M. C., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-41961-9 · Cited by 8
O’Reilly, M. E., Ho, S., Coronel, J., Zhu, L., Liu, W., Xue, C., Kim, E., Cynn, E., Matias, C. V., Soni, R. K., et al. (2024) · Cell Reports · doi:10.1016/j.celrep.2024.114240 · Cited by 7
Deciphering the ghost proteome in ovarian cancer cells by deep proteogenomic characterization
Garcia-del Rio, D. F., Derhourhi, M., Bonnefond, A., Leblanc, S., Guilloy, N., Roucou, X., Eyckerman, S., Gevaert, K., Salzet, M., & Cardon, T. (2024) · Cell Death & Disease · doi:10.1038/s41419-024-07046-1 · Cited by 7
Penning, A., Snoeck, S., Ormaechea, O. R., Ayyildiz, D., Polzer, O., Buitrago-Arango, M., Capobianco, R., de Winter, F., Balusu, S., Verhaagen, J., et al. (2026) · Acta Neuropathologica Communications · doi:10.1186/s40478-026-02228-8 · Cited by 6
ACOT12, a novel factor in the pathogenesis of kidney fibrosis, modulates ACBD5.
Kim, E. H., Kim, M. K., Choe, M., Ryu, J. H., Pak, E. S., Ha, H., & Jin, E.-J. (2025) · Experimental & Molecular Medicine · doi:10.1038/s12276-025-01406-3 · Cited by 6
Yang, S., Hao, J., Ooka, M., & Xia, M. (2026) · Scientific Reports · doi:10.1038/s41598-025-32539-0 · Cited by 5
Redox control of the deubiquitinating enzyme Ubp2 regulates translation during stress
Santos, C. M., Cizubu, B. K., Okonkwo, D. A., Chen, C.-Y., Maske, N., Snyder, N. A., Simões, V., Washington, E. J., & Silva, G. M. (2024) · Journal of Biological Chemistry · doi:10.1016/j.jbc.2024.107870 · Cited by 5
Genomic and genetic insights into speciation and pigment pattern diversification in Danio fishes
Lu, J., Podobnik, M., Huang, J., McCluskey, B. M., McCarthy, S. A., Wood, J., Collins, J., Torrance, J., Sims, Y., Gao, D., et al. (2025) · doi:10.1101/2025.10.17.682988 · Cited by 4
Lee, D., Ahn, J., & Choi, J. (2025) · BMC Bioinformatics · doi:10.1186/s12859-025-06125-0 · Cited by 4
Impact of Acute Endurance Exercise on Alternative Splicing in Skeletal Muscle
Ahn, A., Kim, J. J., Slusher, A. L., Ying, J. Y., Zhang, E. Y., & Ludlow, A. T. (2025) · FASEB BioAdvances · doi:10.1096/fba.2025-00007 · Cited by 4
Pan, G., Huang, M., Fu, S., Wang, Y., He, L., Wu, B., Yang, J., Lin, S., & Fan, Y. (2025) · Scientific Reports · doi:10.1038/s41598-025-06294-1 · Cited by 3
A Systems Biology Analysis of Chronic Lymphocytic Leukemia
Pozzati, G., Zhou, J., Hazan, H., Klement, G. L., Siegelmann, H. T., Tuszynski, J. A., & Rietman, E. A. (2024) · Onco · doi:10.3390/onco4030013 · Cited by 3
Fowler, C. E., O’Hearn, N. A., Salus, G. J., Singh, A., Boutz, P. L., & Lees, J. A. (2025) · iScience · doi:10.1016/j.isci.2025.112965 · Cited by 3
Sanjeev, M., Woodward, L. A., Schiff, M. L., Patton, R. D., Myers, S., Paul, D., Bundschuh, R., & Singh, G. (2025) · Nature Communications · doi:10.1038/s41467-025-63455-6 · Cited by 3
Varella-Branco, E., Shephard, E., Toledo, V. H. C., Ramos, I. C., Lacerda, E. C. M., Carvalho, L. L. M., Fiuza, M. A., Paschalidis, M., Costa, C. I. S., Girardi, A. C. S., et al. (2026) · Molecular Psychiatry · doi:10.1038/s41380-025-03433-y · Cited by 2
Liu, K., Zhang, Z., Su, Y., Ma, X., Wang, J., Yang, Q., Nie, Q., Mo, Z., Zhou, H., Zouboulis, C. C., et al. (2026) · Journal of Nanobiotechnology · doi:10.1186/s12951-026-04291-8 · Cited by 2
Li, Q., Nichols, C., Welner, R. S., Chen, J. Y., Ku, W.-S., & Yue, Z. (2026) · Briefings in Bioinformatics · doi:10.1093/bib/bbag244
“These include Gorilla [ 31], DAVID [ 32], WebGestalt [ 33], EnrichR [ 34], PANTHER Gene List Analysis [ 35], TermMapper [ 36], and g:profiler [ 37], which are frequently used to provide valuable interpretations into high-throughput omics.”
Jedlickova, J., Vajter, M., Barta, T., Black, G., Mares, J., Fichtl, M., Kousal, B., Dudakova, L., & Liskova, P. (2023) · doi:10.1101/2023.02.09.23284763
Metadata
- Authors
- Sherman, B. T., Hao, M., Qiu, J., Jiao, X., Baseler, M. W., Lane, H. C., Imamichi, T., & Chang, W.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2022-03-23
- Volume
- 50
- Issue
- W1
- Pages
- W216-W221
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- OpenAlex
- W4220831425
- Cited by
- 6,142
- References
- 5
- FWCI
- 356.45
- 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.