The Molecular Signatures Database Hallmark Gene Set Collection
Open accessAbstract
The Molecular Signatures Database (MSigDB) is one of the most widely used and comprehensive databases of gene sets for performing gene set enrichment analysis. Since its creation, MSigDB has grown beyond its roots in metabolic disease and cancer to include >10,000 gene sets. These better represent a wider range of biological processes and diseases, but the utility of the database is reduced by increased redundancy across, and heterogeneity within, gene sets. To address this challenge, here we use a combination of automated approaches and expert curation to develop a collection of "hallmark" gene sets as part of MSigDB. Each hallmark in this collection consists of a "refined" gene set, derived from multiple "founder" sets, that conveys a specific biological state or process and displays coherent expression. The hallmarks effectively summarize most of the relevant information of the original founder sets and, by reducing both variation and redundancy, provide more refined and concise inputs for gene set enrichment analysis.
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
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.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the old-dominated spleen B cell clusters, Myc target genes and DNA repair pathways were up-regulated, whereas TRP53 pathway genes were down-regulated.
“Performing gene set enrichment analysis using the MSigDB Hallmark gene sets (Liberzon et al. 2015), we observed that Myc target genes and DNA repair pathways were up-regulated, whereas TRP53 pathway genes were down-regulated (Fig. 4D).”
From Murine single-cell RNA-seq reveals cell-identity- and tissue-specific trajectories of aging (2019) · cites this paper as Liberzon et al. 2015
Gene set enrichment analyses were performed according to standard procedures on two published RNA-seq datasets.
“Gene set enrichment analyses were performed according to standard procedures [39, 40] on two published RNA-seq datasets [31, 48]”
From A gene toolbox for monitoring autophagy transcription (2021) · cites this paper as [40]
Genes upregulated in control reactive astrocytes compared to Ts21 reactive astrocytes are enriched for Hallmark gene sets (DEGs: adj. p < 0.01).
“( F ) Hallmark gene set (81) enrichment plot for genes upregulated in control reactive astrocytes as compared to Ts21 reactive astrocytes (DEGs: adj. p<0.01, Wilcoxon Rank Sum test).”
From Molecular and cellular processes disrupted in the early postnatal Down syndrome prefrontal cortex (2026) · cites this paper as [81]
Carriers of MNAT1 gene were linked to better treatment outcome of FOLFOX.
“Moreover, carriers of MNAT1 gene, which is one of the leading genes in the G2/M checkpoint pathway58, were linked to better treatment outcome of FOLFOX54.”
From Self-supervised learning reveals clinically relevant histomorphological patterns for therapeutic strategies in colon cancer (2025) · cites this paper as [58]
The Results section on matching hallmark enrichment scores to protein phenotypes examines cancer cell lines and protein profiles, not FOLFOX treatment outcomes. Searches for MNAT1 and FOLFOX found no passage in our copy linking MNAT1 carriers to better treatment outcomes. The indexed passages provide no page numbers. (LLM, conf=0.76)
Experimental — accuracy not yet measuredIn the MDP-l,d dataset, hallmark gene sets for inflammatory response and NF-κB signaling were significantly enriched.
“Significant enrichment of hallmark gene sets (33) for inflammatory response and NF-κB signaling were found in the MDP-l,d dataset (Table S8).”
From <i>Enterococcus</i> peptidoglycan remodeling promotes checkpoint inhibitor cancer immunotherapy (2021) · cites this paper as [33]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482 · see citing works
Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625 · see citing works
Self-citationSystematic and integrative analysis of large gene lists using DAVID bioinformatics resources
Huang, D. W., Sherman, B. T., & Lempicki, R. A. (2009) · Nature Protocols · doi:10.1038/nprot.2008.211 · Cited by 35,890 · see citing works
Huang, D. W., Sherman, B. T., & Lempicki, R. A. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkn923 · Cited by 14,108 · see citing works
Ostrom, Q. T., Gittleman, H. R., Farah, P., Ondracek, A., Chen, Y., Wolinsky, Y., Stroup, N. E., Kruchko, C. A., & Barnholtz‐Sloan, J. S. (2013) · Neuro-Oncology · doi:10.1093/neuonc/not151 · Cited by 12,049 · see citing works
Mootha, V. K., Lindgren, C. M., Eriksson, K.-F., Subramanian, A., Sihag, S., Lehar, J., Puigserver, P., Carlsson, E., Ridderstråle, M., Laurila, E., et al. (2003) · Nature Genetics · doi:10.1038/ng1180 · Cited by 10,197 · see citing works
Self-citationThe basics of epithelial-mesenchymal transition
Kalluri, R., & Weinberg, R. A. (2009) · Journal of Clinical Investigation · doi:10.1172/jci39104 · Cited by 10,196 · see citing works
The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity
Barretina, J., Caponigro, G., Stransky, N., Venkatesan, K., Margolin, A. A., Kim, S., Wilson, C. J., Lehár, J., Kryukov, G. V., Sonkin, D., et al. (2012) · Nature · doi:10.1038/nature11003 · Cited by 7,950 · see citing works
Self-citationVerhaak, R. G. W., Hoadley, K. A., Purdom, E., Wang, V., Qi, Y., Wilkerson, M. D., Miller, C. R., Ding, L., Golub, T., Mesirov, J. P., et al. (2010) · Cancer Cell · doi:10.1016/j.ccr.2009.12.020 · Cited by 7,575 · see citing works
Self-citationMolecular signatures database (MSigDB) 3.0
Liberzon, A., Subramanian, A., Pinchback, R., Thorvaldsdóttir, H., Tamayo, P., & Mesirov, J. P. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr260 · Cited by 7,111 · see citing works
Self-citationSystematic RNA interference reveals that oncogenic KRAS-driven cancers require TBK1
Barbie, D. A., Tamayo, P., Boehm, J. S., Kim, S. Y., Moody, S. E., Dunn, I. F., Schinzel, A. C., Sandy, P., Meylan, E., Scholl, C., et al. (2009) · Nature · doi:10.1038/nature08460 · Cited by 3,869 · see citing works
Self-citationBiomarkers for epithelial-mesenchymal transitions
Zeisberg, M., & Neilson, E. G. (2009) · Journal of Clinical Investigation · doi:10.1172/jci36183 · Cited by 2,299 · cited 1× · see citing works
“3E)— N-cadherin is a marker of mesenchymal cells (Zeisberg and Neilson, 2009) and the epithelial-mesenchymal transition (EMT) (Kalluri and Weinberg, 2009).”
Metagenes and molecular pattern discovery using matrix factorization
Brunet, J.-P., Tamayo, P., Golub, T. R., & Mesirov, J. P. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0308531101 · Cited by 2,183 · see citing works
Self-citationMonti, S., Tamayo, P., Mesirov, J., & Golub, T. (2003) · Machine Learning · doi:10.1023/a:1023949509487 · Cited by 2,116 · see citing works
Self-citationNCBI GEO: mining tens of millions of expression profiles--database and tools update
Barrett, T., Troup, D. B., Wilhite, S. E., Ledoux, P., Rudnev, D., Evangelista, C., Kim, I. F., Soboleva, A., Tomashevsky, M., & Edgar, R. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkl887 · Cited by 1,524 · see citing works
The JAK-STAT Pathway at Twenty
Stark, G. R., & Darnell, J. E., Jr. (2012) · Immunity · doi:10.1016/j.immuni.2012.03.013 · Cited by 1,523 · see citing works
Targeting the TGFβ signalling pathway in disease
Akhurst, R. J., & Hata, A. (2012) · Nature Reviews Drug Discovery · doi:10.1038/nrd3810 · Cited by 1,466 · see citing works
GSEA-P : a desktop application for Gene Set Enrichment Analysis
Subramanian, A., Kuehn, H., Gould, J., Tamayo, P., & Mesirov, J. P. (2007) · Bioinformatics · doi:10.1093/bioinformatics/btm369 · Cited by 1,379 · see citing works
Self-citationBlood Vessel Formation: What Is Its Molecular Basis?
Folkman, J., & D'Amore, P. A. (1996) · Cell · doi:10.1016/s0092-8674(00)81810-3 · Cited by 1,227 · see citing works
Efron, B. (2010) · Cambridge University Press eBooks · doi:10.1017/cbo9780511761362 · Cited by 820 · see citing works
LEVANDOWSKY, M., & Winter, D. J. (1971) · Nature · doi:10.1038/234034a0 · Cited by 744 · see citing works
Cho, Y., Tsherniak, A., Tamayo, P., Santagata, S., Ligon, A. H., Greulich, H. E., Berhoukim, R., Amani, V. M., Goumnerova, L., Eberhart, C. G., et al. (2010) · Journal of Clinical Oncology · doi:10.1200/jco.2010.28.5148 · Cited by 714 · see citing works
Self-citationMedulloblastomics: the end of the beginning
Northcott, P. A., Jones, D., Kool, M., Robinson, G. W., Gilbertson, R. J., Cho, Y., Pomeroy, S. L., Korshunov, A., Lichter, P., Taylor, M. D., et al. (2012) · Nature reviews. Cancer · doi:10.1038/nrc3410 · Cited by 661 · see citing works
fastcluster : Fast Hierarchical, Agglomerative Clustering Routines for R and Python
Müllner, D. (2013) · Journal of Statistical Software · doi:10.18637/jss.v053.i09 · Cited by 651 · see citing works
Genenames.org: the HGNC resources in 2015
Gray, K. A., Yates, B., Seal, R. L., Wright, M. W., & Bruford, E. A. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku1071 · Cited by 493 · see citing works
ArrayExpress update—trends in database growth and links to data analysis tools
Rustici, G., Kolesnikov, N. N., Brandizi, M., Burdett, T., Dylag, M., Emam, I., Farne, A., Hastings, E., Ison, J., Keays, M., et al. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1174 · Cited by 368 · see citing works
Combining Independent Tests of Significance*
Birnbaum, A. (1954) · Journal of the American Statistical Association · doi:10.1080/01621459.1954.10483521 · Cited by 354 · see citing works
The Androgen Receptor in Health and Disease
Μatsumoto, T., Sakari, M., Okada, M., Yokoyama, A., Takahashi, S., Kouzmenko, A., & Kato, S. (2012) · Annual Review of Physiology · doi:10.1146/annurev-physiol-030212-183656 · Cited by 268 · see citing works
Dominant Negative Stat3 Mutant Inhibits Interleukin-6-induced Jak-STAT Signal Transduction (*)
Kaptein, A., Paillard, V., & Saunders, M. (1996) · Journal of Biological Chemistry · doi:10.1074/jbc.271.11.5961 · Cited by 264 · see citing works
Xingbin, W., Kang, D., Shen, K., Song, C., Lu, S., Chang, L., Liao, S. G., Huo, Z., Tang, S., Ding, Y., et al. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts485 · Cited by 203 · see citing works
Reverse-phase protein lysate microarrays for cell signaling analysis
Spurrier, B., Ramalingam, S., & Nishizuka, S. (2008) · Nature Protocols · doi:10.1038/nprot.2008.179 · Cited by 183 · see citing works
Mitosis and apoptosis: how is the balance set?
Topham, C. H., & Taylor, S. S. (2013) · Current Opinion in Cell Biology · doi:10.1016/j.ceb.2013.07.003 · Cited by 177 · see citing works
The role of Stat5 transcription factors as tumor suppressors or oncogenes
Ferbeyre, G., & Moriggl, R. (2010) · Biochimica et Biophysica Acta (BBA) - Reviews on Cancer · doi:10.1016/j.bbcan.2010.10.004 · Cited by 123 · see citing works
Lois de distribution florale dans la zone alpine
Jaccard, P. (1902) · E-Periodica · doi:10.5169/seals-266762 · Cited by 123 · see citing works
Large-Scale Inference: Empirical Bayes Methods for Estimation, Testing, and Prediction
Robert, C. P. (2012) · CHANCE · doi:10.1080/09332480.2012.726568 · Cited by 115 · see citing works
Karsy, M. J., Gelbman, M., Shah, P., Balumbu, O., MOY, F. H., & Arslan, E. (2012) · Folia Neuropathologica · doi:10.5114/fn.2012.32361 · Cited by 108 · see citing works
Analyzing the Large Number of Variables in Biomedical Imagery: A Brief Review
Good, P. (2011) · Journal of Biopharmaceutical Statistics · doi:10.1080/10543406.2011.607772 · Cited by 5 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
ShinyGO: a graphical gene-set enrichment tool for animals and plants
Ge, S. X., Jung, D., & Yao, R. (2020) · Bioinformatics · doi:10.1093/bioinformatics/btz931 · Cited by 5,270 · see citing works
Genetic effects on gene expression across human tissues
GTEx Consortium (2017) · Nature · doi:10.1038/nature24277 · Cited by 4,036 · see citing works
eQTLGen, Wray, N. R., 23andMe, the Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Ripke, S., Mattheisen, M., Trzaskowski, M., Byrne, E. M., Abdellaoui, A., Adams, M. J., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0090-3 · Cited by 3,005 · see citing works
Single-cell landscape of bronchoalveolar immune cells in patients with COVID-19
Liao, M., Liu, Y., Yuan, J., Wen, Y., Xu, G., Zhao, J., Cheng, L., Li, J., Wang, X., Wang, F., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-0901-9 · Cited by 2,614 · see citing works
C2c2 is a single-component programmable RNA-guided RNA-targeting CRISPR effector
Abudayyeh, O. O., Gootenberg, J. S., Konermann, S., Joung, J., Slaymaker, I. M., Cox, D. B. T., Shmakov, S., Makarova, K. S., Semenova, E., Станиславович, М. Л., et al. (2016) · Science · doi:10.1126/science.aaf5573 · Cited by 2,328 · see citing works
Reimand, J., Isserlin, R., Voisin, V., Kucera, M., Tannus-Lopes, C., Rostamianfar, A., Wadi, L., Meyer, M., Wong, J., Xu, C., et al. (2019) · Nature Protocols · doi:10.1038/s41596-018-0103-9 · Cited by 1,970 · see citing works
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 · see citing works
iDEP: an integrated web application for differential expression and pathway analysis of RNA-Seq data
Ge, X., Son, E., & Yao, R. (2018) · BMC Bioinformatics · doi:10.1186/s12859-018-2486-6 · Cited by 1,643 · see citing works
Severe COVID-19 Is Marked by a Dysregulated Myeloid Cell Compartment
Schulte-Schrepping, J., Reusch, N., Paclik, D., Baßler, K., Schlickeiser, S., Zhang, B., Krämer, B., Krammer, T., Brumhard, S., Bonaguro, L., et al. (2020) · Cell · doi:10.1016/j.cell.2020.08.001 · Cited by 1,461 · see citing works
Lineage tracking reveals dynamic relationships of T cells in colorectal cancer
Zhang, L., Yu, X., Zheng, L., Zhang, Y., Li, Y., Fang, Q., Gao, R., Kang, B., Zhang, Q., Huang, J. Y., et al. (2018) · Nature · doi:10.1038/s41586-018-0694-x · Cited by 1,505 · see citing works
A pan-cancer single-cell transcriptional atlas of tumor infiltrating myeloid cells
Cheng, S., Li, Z., Gao, R., Xing, B., Gao, Y., Yang, Y., Qin, S., Zhang, L., Ouyang, H., Du, P., et al. (2021) · Cell · doi:10.1016/j.cell.2021.01.010 · Cited by 1,601 · see citing works
Single-cell transcriptional diversity is a hallmark of developmental potential
Gulati, G. S., Sikandar, S. S., Wesche, D. J., Manjunath, A., Bharadwaj, A., Berger, M. J., Ilagan, F., Kuo, A. H., Hsieh, R. W., Cai, S., et al. (2020) · Science · doi:10.1126/science.aax0249 · Cited by 1,571 · see citing works
PanglaoDB: a web server for exploration of mouse and human single-cell RNA sequencing data
Franzén, O., Gan, L.-M., & Björkegren, J. L. M. (2019) · Database · doi:10.1093/database/baz046 · Cited by 1,551 · see citing works
Intra- and Inter-cellular Rewiring of the Human Colon during Ulcerative Colitis
Smillie, C. S., Biton, M., Ordovás-Montañés, J., Sullivan, K. M., Burgin, G., Graham, D. B., Herbst, R. H., Rogel, N., Slyper, M., Waldman, J., et al. (2019) · Cell · doi:10.1016/j.cell.2019.06.029 · Cited by 1,386 · see citing works
Conserved pan-cancer microenvironment subtypes predict response to immunotherapy
Bagaev, A., Kotlov, N., Nomie, K., Svekolkin, V., Gafurov, A., Isaeva, O., Osokin, N., Kozlov, I., Frenkel, F., Gancharova, O., et al. (2021) · Cancer Cell · doi:10.1016/j.ccell.2021.04.014 · Cited by 1,302 · see citing works
Zhang, F., Wei, K., Slowikowski, K., Fonseka, C. Y., Rao, D. A., Kelly, S., Goodman, S. M., Tabechian, D. A., Hughes, L. B., Salomon-Escoto, K., et al. (2019) · Nature Immunology · doi:10.1038/s41590-019-0378-1 · Cited by 1,380 · see citing works
Genomic correlates of response to immune checkpoint therapies in clear cell renal cell carcinoma
Miao, D., Margolis, C. A., Gao, W., Voss, M. H., Li, W., Martini, D. J., Norton, C., Bossé, D., Wankowicz, S. M., Cullen, D., et al. (2018) · Science · doi:10.1126/science.aan5951 · Cited by 1,249 · see citing works
Targeting KRAS mutant cancers with a covalent G12C-specific inhibitor
Janes, M. R., Zhang, J., Li, L.-S., Hansen, R., Peters, U., Guo, X., Chen, Y., Babbar, A., Firdaus, S. J., Darjania, L., et al. (2018) · Cell · doi:10.1016/j.cell.2018.01.006 · Cited by 1,172 · see citing works
Multimodal Analysis of Composition and Spatial Architecture in Human Squamous Cell Carcinoma
Ji, A. L., Rubin, A. J., Thrane, K., Jiang, S., Reynolds, D. L., Meyers, R. M., Guo, M. G., George, B. M., Mollbrink, A., Bergenstråhle, J., et al. (2020) · Cell · doi:10.1016/j.cell.2020.05.039 · Cited by 1,117 · see citing works
“Right, Violin plots of TSK-proximal stroma scores (n = 209 genes, Wilcoxon rank-sum test, adjusted p value < 0.05) by cell types in scRNA-seq data (STAR Methods). ll OPEN ACCESS Resource”
BackgroundInfluentialSpatiotemporal Immune Landscape of Colorectal Cancer Liver Metastasis at Single-Cell Level
Wu, Y., Yang, S., Ma, J., Chen, Z., Song, G., Rao, D., Cheng, Y., Huang, S., Liu, Y., Jiang, S., et al. (2021) · Cancer Discovery · doi:10.1158/2159-8290.cd-21-0316 · Cited by 1,199 · see citing works
HMDD v2.0: a database for experimentally supported human microRNA and disease associations
Li, Y., Qiu, C., Tu, J., Geng, B., Yang, J., Jiang, T., & Cui, Q. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt1023 · Cited by 1,164 · see citing works
In vivo CRISPR screening identifies Ptpn2 as a cancer immunotherapy target
Manguso, R. T., Pope, H. W., Zimmer, M. D., Brown, F. D., Yates, K. B., Miller, B. C., Collins, N. B., Bi, K., LaFleur, M. W., Juneja, V. R., et al. (2017) · Nature · doi:10.1038/nature23270 · Cited by 1,147 · see citing works
Wightman, D. P., Jansen, I. E., Savage, J. E., Shadrin, A. A., Bahrami, S., Holland, D., Rongve, A., Børte, S., Winsvold, B. S., Drange, O. K., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00921-z · Cited by 1,011 · see citing works
Chemoresistance Evolution in Triple-Negative Breast Cancer Delineated by Single-Cell Sequencing
Kim, C. R., Gao, R., Sei, E., Brandt, R., Hartman, J., Hatschek, T., Crosetto, N., Foukakis, T., & Navin, N. E. (2018) · Cell · doi:10.1016/j.cell.2018.03.041 · Cited by 1,091 · see citing works
UCell: robust and scalable single-cell gene signature scoring
Andreatta, M., & Carmona, S. J. (2021) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2021.06.043 · Cited by 1,104 · see citing works
Modulation of Myelopoiesis Progenitors Is an Integral Component of Trained Immunity
Mitroulis, I., Ruppova, K., Wang, B., Chen, L.-S., Grzybek, M., Grinenko, T., Eugster, A., Troullinaki, M., Palladini, A., Kourtzelis, I., et al. (2018) · Cell · doi:10.1016/j.cell.2017.11.034 · Cited by 1,100 · see citing works
DIABLO: an integrative approach for identifying key molecular drivers from multi-omics assays
Singh, A., Shannon, C. P., Gautier, B., Rohart, F., Vacher, M. A., Tebbutt, S. J., & Cao, K. L. (2019) · Bioinformatics · doi:10.1093/bioinformatics/bty1054 · Cited by 1,076 · see citing works
Sun, D., Wang, J., Han, Y., Dong, X., Ge, J., Zheng, R., Shi, X., Wang, B., Li, Z., Ren, P., et al. (2020) · Nucleic Acids Research · doi:10.1093/nar/gkaa1020 · Cited by 1,076 · see citing works
Disease-associated astrocytes in Alzheimer’s disease and aging
Habib, N., McCabe, C., Medina, S., Varshavsky, M., Kitsberg, D., Dvir-Szternfeld, R., Green, G., Dionne, D., Nguyen, L., Marshall, J. L., et al. (2020) · Nature Neuroscience · doi:10.1038/s41593-020-0624-8 · Cited by 1,009 · see citing works
Braun, D. A., Hou, Y., Bakouny, Z., Ficial, M., Sant’ Angelo, M., Forman, J., Ross-Macdonald, P., Berger, A. C., Jegede, O. A., Elagina, L., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-0839-y · Cited by 992 · see citing works
CancerSEA: a cancer single-cell state atlas
Yuan, H., Yan, M., Zhang, G., Liu, W., Deng, C., Liao, G., Xu, L., Luo, T., Yan, H., Long, Z., et al. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky939 · Cited by 1,036 · see citing works
Klemm, F., Maas, R. R., Bowman, R. L., Kornete, M., Soukup, K., Nassiri, S., Brouland, J., Iacobuzio–Donahue, C. A., Brennan, C. W., Tabar, V. S., et al. (2020) · Cell · doi:10.1016/j.cell.2020.05.007 · Cited by 1,050 · see citing works
Liu, D., Schilling, B., Liu, D., Sucker, A., Livingstone, E., Jerby-Arnon, L., Zimmer, L., Gutzmer, R., Satzger, I., Loquai, C., et al. (2019) · Nature Medicine · doi:10.1038/s41591-019-0654-5 · Cited by 1,039 · see citing works
Genetic and transcriptional evolution alters cancer cell line drug response
Ben-David, U., Siranosian, B., Ha, G., Tang, H., Oren, Y., Hinohara, K., Strathdee, C. A., Dempster, J., Lyons, N. J., Burns, R., et al. (2018) · Nature · doi:10.1038/s41586-018-0409-3 · Cited by 931 · see citing works
Self-citationQi, J., Sun, H., Zhang, Y., Wang, Z., Xun, Z., Li, Z., Ding, X., Bao, R., Hong, L., Jia, W., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-29366-6 · Cited by 983 · see citing works
Quantitative Proteomics of the Cancer Cell Line Encyclopedia
Nusinow, D. P., Szpyt, J., Ghandi, M., Rose, C. M., McDonald, E. R., Kalocsay, M., Jané-Valbuena, J., Gelfand, E., Schweppe, D. K., Jedrychowski, M., et al. (2020) · Cell · doi:10.1016/j.cell.2019.12.023 · Cited by 957 · see citing works
Self-citationDelineating copy number and clonal substructure in human tumors from single-cell transcriptomes
Gao, R., Bai, S., Henderson, Y. C., Lin, Y., Schalck, A. P., Yan, Y., Kumar, T., Hu, M. S., Sei, E., Davis, A., et al. (2021) · Nature Biotechnology · doi:10.1038/s41587-020-00795-2 · Cited by 931 · see citing works
Lineage-dependent gene expression programs influence the immune landscape of colorectal cancer
Lee, H., Hong, Y., Etlioglu, H. E., Cho, Y. B., Pomella, V., den Bosch, B. V., Vanhecke, J., Verbandt, S., Hong, H.-K., Min, J.-W., et al. (2020) · Nature Genetics · doi:10.1038/s41588-020-0636-z · Cited by 916 · see citing works
Voorwerk, L., Slagter, M., Horlings, H. M., Sikorska, K., de Vijver, K. K. V., de Maaker, M., Nederlof, I., Kluin, R. J. C., Warren, S., Ong, S., et al. (2019) · Nature Medicine · doi:10.1038/s41591-019-0432-4 · Cited by 912 · see citing works
Spatially organized multicellular immune hubs in human colorectal cancer
Pelka, K., Hofree, M., Chen, J. H., Sarkizova, S., Pirl, J. D., Jorgji, V., Bejnood, A., Dionne, D. A., Ge, W. H., Xu, K. H., et al. (2021) · Cell · doi:10.1016/j.cell.2021.08.003 · Cited by 902 · see citing works
Proteogenomic Characterization Reveals Therapeutic Vulnerabilities in Lung Adenocarcinoma
Gillette, M. A., Satpathy, S., Cao, S., Dhanasekaran, S. M., Vasaikar, S. V., Krug, K., Petralia, F., Li, Y., Liang, W.-W., Reva, B., et al. (2020) · Cell · doi:10.1016/j.cell.2020.06.013 · Cited by 820 · see citing works
Self-citationCOVID-19 immune features revealed by a large-scale single-cell transcriptome atlas
Ren, X., Wen, W., Fan, X., Hou, W., Su, B., Cai, P., Li, J., Liu, Y., Tang, F., Zhang, F., et al. (2021) · Cell · doi:10.1016/j.cell.2021.01.053 · Cited by 865 · see citing works
Integrative clinical genomics of metastatic cancer
Robinson, D. R., Wu, Y.-M., Lonigro, R. J., Vats, P., Cobain, E., Everett, J., Cao, X., Rabban, E., Kumar-Sinha, C., Raymond, V., et al. (2017) · Nature · doi:10.1038/nature23306 · Cited by 863 · see citing works
Jansen, P. R., Watanabe, K., Stringer, S., Skene, N., Bryois, J., Hammerschlag, A. R., de Leeuw, C., Benjamins, J. S., Muñoz‐Manchado, A. B., Nagel, M., et al. (2019) · Nature Genetics · doi:10.1038/s41588-018-0333-3 · Cited by 839 · see citing works
Single-cell multi-omics analysis of the immune response in COVID-19
Cambridge Institute of Therapeutic Immunology and Infectious Disease-National Institute of Health Research (CITIID-NIHR) COVID-19 BioResource Collaboration, Stephenson, E., Reynolds, G., Botting, R. A., Calero-Nieto, F. J., Morgan, M. D., Tuong, Z. K., Bach, K., Sungnak, W., Worlock, K. B., et al. (2021) · Nature Medicine · doi:10.1038/s41591-021-01329-2 · Cited by 742 · see citing works
HMDD v3.0: a database for experimentally supported human microRNA–disease associations
Huang, Z., Shi, J., Gao, Y., Cui, C., Zhang, S., Li, J., Zhou, Y., & Cui, Q. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky1010 · Cited by 812 · see citing works
Proteogenomic Analysis of Human Colon Cancer Reveals New Therapeutic Opportunities
Vasaikar, S., Huang, C., Wang, X., Petyuk, V. A., Savage, S. R., Wen, B., Dou, Y., Zhang, Y., Shi, Z., Arshad, O. A., et al. (2019) · Cell · doi:10.1016/j.cell.2019.03.030 · Cited by 799 · see citing works
Loss of ADAR1 in tumours overcomes resistance to immune checkpoint blockade
Ishizuka, J. J., Manguso, R. T., Cheruiyot, C. K., Bi, K., Panda, A., Iracheta-Vellve, A., Miller, B. C., Du, P. P., Yates, K. B., Dubrot, J., et al. (2019) · Nature · doi:10.1038/s41586-018-0768-9 · Cited by 697 · see citing works
Patient-derived xenografts undergo mouse-specific tumor evolution
Ben-David, U., Ha, G., Tseng, Y.-Y., Greenwald, N. F., Oh, C., Shih, J., McFarland, J. M., Wong, B., Boehm, J. S., Beroukhim, R., et al. (2017) · Nature Genetics · doi:10.1038/ng.3967 · Cited by 716 · see citing works
Yan, H. H. N., Siu, H. C., Law, S., Ho, S. L., Yue, S. S. K., Tsui, W. Y., Chan, D., Chan, A. S., Ma, S., Lam, K. O., et al. (2018) · Cell Stem Cell · doi:10.1016/j.stem.2018.09.016 · Cited by 724 · see citing works
Hudson, W. H., Gensheimer, J., Hashimoto, M., Wieland, A., Valanparambil, R. M., Li, P., Lin, J.-X., Konieczny, B. T., Im, S. J., Freeman, G. J., et al. (2019) · Immunity · doi:10.1016/j.immuni.2019.11.002 · Cited by 656 · see citing works
The tumor microenvironment underlies acquired resistance to CSF-1R inhibition in gliomas
Quail, D. F., Bowman, R. L., Akkari, L., Quick, M. L., Schuhmacher, A. J., Huse, J. T., Holland, E. C., Sutton, J. C., & Joyce, J. A. (2016) · Science · doi:10.1126/science.aad3018 · Cited by 669 · see citing works
The STRING database in 2025: protein networks with directionality of regulation
Szklarczyk, D., Nastou, K. C., Koutrouli, M., Kirsch, R. L., Mehryary, F., Hachilif, R., Hu, D., Peluso, M. E., Huang, Q. D., Fang, T., et al. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkae1113 · Cited by 856 · see citing works
Proteogenomic and metabolomic characterization of human glioblastoma
Wang, L.-B., Karpova, A., Gritsenko, M. A., Kyle, J. E., Cao, S., Li, Y., Rykunov, D., Colaprico, A., Rothstein, J. H., Hong, R., et al. (2021) · Cancer Cell · doi:10.1016/j.ccell.2021.01.006 · Cited by 661 · see citing works
Self-citationTumor immunoevasion by the conversion of effector NK cells into type 1 innate lymphoid cells
Gao, Y., Souza-Fonseca-Guimarães, F., Bald, T., Ng, S. S., Young, A., Ngiow, S. F., Rautela, J., Straube, J., Waddell, N., Blake, S. J., et al. (2017) · Nature Immunology · doi:10.1038/ni.3800 · Cited by 654 · see citing works
Multi-omic machine learning predictor of breast cancer therapy response
Sammut, S.-J., Crispin-Ortuzar, M., Chin, S.-F., Provenzano, E., Bardwell, H. A., Ma, W., Cope, W., Dariush, A., Dawson, S.-J., Abraham, J. E., et al. (2022) · Nature · doi:10.1038/s41586-021-04278-5 · Cited by 654 · see citing works
Aung, K. L., Fischer, S. E., Denroche, R. E., Jang, G.-H., Dodd, A., Creighton, S., Southwood, B., Liang, S.-B., Chadwick, D., Zhang, A., et al. (2018) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-17-2994 · Cited by 618 · see citing works
Innate Immune Training of Granulopoiesis Promotes Anti-tumor Activity
Kalafati, L., Kourtzelis, I., Schulte-Schrepping, J., Li, X., Hatzioannou, A., Grinenko, T., Hagag, E., Sinha, A., Has, C., Dietz, S., et al. (2020) · Cell · doi:10.1016/j.cell.2020.09.058 · Cited by 648 · see citing works
A Potent and Selective Small-Molecule Degrader of STAT3 Achieves Complete Tumor Regression In Vivo
Bai, L., Zhou, H., Xu, R., Zhao, Y., Chinnaswamy, K., McEachern, D., Chen, J., Yang, C.-Y., Liu, Z., Wang, M., et al. (2019) · Cancer Cell · doi:10.1016/j.ccell.2019.10.002 · Cited by 652 · see citing works
Comprehensive analysis of normal adjacent to tumor transcriptomes
Aran, D., Camarda, R., Odegaard, J. I., Paik, H., Oskotsky, B., Krings, G., Goga, A., Sirota, M., & Butte, A. J. (2017) · Nature Communications · doi:10.1038/s41467-017-01027-z · Cited by 619 · see citing works
Tumor and immune reprogramming during immunotherapy in advanced renal cell carcinoma
Bi, K., He, M. X., Bakouny, Z., Kanodia, A., Napolitano, S., Wu, J., Grimaldi, G., Braun, D. A., Cuoco, M. S., Mayorga, A., et al. (2021) · Cancer Cell · doi:10.1016/j.ccell.2021.02.015 · Cited by 613 · see citing works
Chu, T., Wang, Z., Pe’er, D., & Danko, C. G. (2022) · Nature Cancer · doi:10.1038/s43018-022-00356-3 · Cited by 612 · see citing works
KRAS-IRF2 axis drives immune suppression and immune therapy resistance in colorectal cancer
Liao, W., Overman, M. J., Boutin, A. T., Shang, X., Zhao, D., Dey, P., Li, J., Wang, G., Lan, Z., Li, J., et al. (2019) · Cancer Cell · doi:10.1016/j.ccell.2019.02.008 · Cited by 617 · see citing works
Multilineage communication regulates human liver bud development from pluripotency
Camp, J. G., Sekine, K., Gerber, T., Loeffler-Wirth, H., Binder, H., Gac, M., Kanton, S., Kageyama, J., Damm, G., Seehofer, D., et al. (2017) · Nature · doi:10.1038/nature22796 · Cited by 621 · see citing works
Large-Scale Multi-omic Analysis of COVID-19 Severity
Overmyer, K. A., Shishkova, E., Miller, I. J., Balnis, J., Bernstein, M. N., Peters-Clarke, T. M., Meyer, J. G., Quan, Q., Muehlbauer, L. K., Trujillo, E. A., et al. (2020) · Cell Systems · doi:10.1016/j.cels.2020.10.003 · Cited by 584 · see citing works
Yang, Z., Yan, C., Ma, J., Peng, P., Ren, X., Cai, S., Shen, X., Wu, Y. C., Zhang, S., Wang, X., et al. (2023) · Nature Metabolism · doi:10.1038/s42255-022-00710-w · Cited by 615 · see citing works
Inactivation of CDK12 Delineates a Distinct Immunogenic Class of Advanced Prostate Cancer
Wu, Y.-M., Cieslik, M. P., Lonigro, R. J., Vats, P., Reimers, M. A., Cao, X., Yu, N., Wang, L., Kunju, L. P., Sarkar, N. D., et al. (2018) · Cell · doi:10.1016/j.cell.2018.04.034 · Cited by 600 · see citing works
Identification of the Human Skeletal Stem Cell
Chan, C. K. F., Gulati, G. S., Sinha, R., Vincent-Tompkins, J., Lopez, M., Carter, A. C., Ransom, R. C., Reinisch, A., Wearda, T. L., Murphy, M. P., et al. (2018) · Cell · doi:10.1016/j.cell.2018.07.029 · Cited by 602 · see citing works
Functionally distinct disease-associated fibroblast subsets in rheumatoid arthritis
Mizoguchi, F., Slowikowski, K., Wei, K., Marshall, J. L., Rao, D. A., Chang, S. K., Nguyen, H., Noss, E. H., Turner, J. D., Earp, B. E., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-02892-y · Cited by 599 · see citing works
Vardhana, S. A., Hwee, M. A., Berisa, M., Wells, D. K., Yost, K. E., King, B., Smith, M., Herrera, P. S., Chang, H. Y., Satpathy, A. T., et al. (2020) · Nature Immunology · doi:10.1038/s41590-020-0725-2 · Cited by 575 · see citing works
Bock, C., Datlinger, P., Chardon, F. M., Coelho, M. A., Dong, M. B., Lawson, K. A., Lu, T., Maroc, L., Norman, T. M., Song, B., et al. (2022) · Nature Reviews Methods Primers · doi:10.1038/s43586-021-00093-4 · Cited by 591 · see citing works
Tsuchida, T., Lee, Y. A., Fujiwara, N., Ybanez, M., Allen, B., Martins, S., Fiel, M. I., Goossens, N., Chou, H.-I., Hoshida, Y., et al. (2018) · Journal of Hepatology · doi:10.1016/j.jhep.2018.03.011 · Cited by 583 · see citing works
SARS-CoV-2 Disrupts Splicing, Translation, and Protein Trafficking to Suppress Host Defenses
Banerjee, A. K., Blanco, M. R., Bruce, E. A., Honson, D. D., Chen, L. M., Chow, A., Bhat, P., Ollikainen, N., Quinodoz, S. A., Loney, C., et al. (2020) · Cell · doi:10.1016/j.cell.2020.10.004 · Cited by 583 · see citing works
Proteogenomic characterization of pancreatic ductal adenocarcinoma
Cao, L., Huang, C., Cui Zhou, D., Hu, Y., Lih, T. M., Savage, S. R., Krug, K., Clark, D. J., Schnaubelt, M., Chen, L., et al. (2021) · Cell · doi:10.1016/j.cell.2021.08.023 · Cited by 578 · see citing works
Self-citationMolecular Subsets in Renal Cancer Determine Outcome to Checkpoint and Angiogenesis Blockade
Motzer, R. J., Banchereau, R., Hamidi, H., Powles, T. B., McDermott, D. F., Atkins, M. B., Escudier, B. J., Liu, L.-F., Leng, N., Abbas, A. R., et al. (2020) · Cancer Cell · doi:10.1016/j.ccell.2020.10.011 · Cited by 568 · see citing works
Kotliar, D., Veres, A., Nagy, M. A., Tabrizi, S., Hodis, E., Melton, D. A., & Sabeti, P. C. (2019) · eLife · doi:10.7554/elife.43803 · Cited by 638 · see citing works
SARS-CoV-2 infects and replicates in cells of the human endocrine and exocrine pancreas
Müller, J. A., Groß, R. M., Conzelmann, C., Krüger, J., Merle, U., Steinhart, J., Weil, T., Koepke, L., Bozzo, C. P., Read, C., et al. (2021) · Nature Metabolism · doi:10.1038/s42255-021-00347-1 · Cited by 555 · see citing works
The Functional Impact of Alternative Splicing in Cancer
Climente-González, H., Porta‐Pardo, E., Godzik, A., & Eyras, E. (2017) · Cell Reports · doi:10.1016/j.celrep.2017.08.012 · Cited by 546 · see citing works
Proteogenomic Landscape of Breast Cancer Tumorigenesis and Targeted Therapy
Krug, K., Jaehnig, E. J., Satpathy, S., Blumenberg, L. M., Karpova, A. Y., Anurag, M., Miles, G., Mertins, P., Geffen, Y., Tang, L. C., et al. (2020) · Cell · doi:10.1016/j.cell.2020.10.036 · Cited by 532 · see citing works
Self-citationInterpretation of T cell states from single-cell transcriptomics data using reference atlases
Andreatta, M., Corría-Osorio, J., Müller, S., Cubas, R. A., Coukos, G., & Carmona, S. J. (2021) · Nature Communications · doi:10.1038/s41467-021-23324-4 · Cited by 525 · see citing works
DNA methylation loss promotes immune evasion of tumours with high mutation and copy number load
Jung, H., Kim, H. S., Kim, J. Y., Sun, J., Ahn, J. S., Ahn, M., Park, K., Esteller, M., Lee, S., & Choi, J. K. (2019) · Nature Communications · doi:10.1038/s41467-019-12159-9 · Cited by 537 · see citing works
Host-Viral Infection Maps Reveal Signatures of Severe COVID-19 Patients
Bost, P., Giladi, A., Liu, Y., Bendjelal, Y., Xu, G., David, E., Blecher-Gonen, R., Cohen, M., Medaglia, C., Li, H., et al. (2020) · Cell · doi:10.1016/j.cell.2020.05.006 · Cited by 471 · see citing works
Marin, D., Li, Y., Başar, R., Rafei, H., Daher, M., Dou, J., Mohanty, V., Dede, M., Nieto, Y., Uprety, N., et al. (2024) · Nature Medicine · doi:10.1038/s41591-023-02785-8 · Cited by 458 · see citing works
Colorectal Cancer Cells Enter a Diapause-like DTP State to Survive Chemotherapy
Rehman, S. K., Haynes, J., Collignon, E., Brown, K. R., Wang, Y., Nixon, A. M. L., Bruce, J. P., Wintersinger, J. A., Singh Mer, A., Lo, E. B. L., et al. (2021) · Cell · doi:10.1016/j.cell.2020.11.018 · Cited by 495 · see citing works
Loss of p53 triggers WNT-dependent systemic inflammation to drive breast cancer metastasis
Wellenstein, M. D., Coffelt, S. B., Duits, D. E. M., van Miltenburg, M. H., Slagter, M., de Rink, I., Henneman, L., Kas, S. M., Prekovic, S., Hau, C.-S., et al. (2019) · Nature · doi:10.1038/s41586-019-1450-6 · Cited by 500 · see citing works
Motzer, R. J., Robbins, P. B., Powles, T., Albiges, L., Haanen, J. B., Larkin, J., Mu, X. J., Ching, K. A., Uemura, M., Pal, S. K., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-1044-8 · Cited by 518 · see citing works
Genomic landscape of lung adenocarcinoma in East Asians
Chen, J., Yang, H., Teo, A. S. M., Amer, L. B., Sherbaf, F. G., Tan, C. Q., Alvarez, J. J. S., Lu, B., Lim, J. Q., Takano, A. M., et al. (2020) · Nature Genetics · doi:10.1038/s41588-019-0569-6 · Cited by 511 · see citing works
Extending support for mouse data in the Molecular Signatures Database (MSigDB)
Castanza, A. S., Recla, J. M., Eby, D., Thorvaldsdóttir, H., Bult, C. J., & Mesirov, J. P. (2023) · Nature Methods · doi:10.1038/s41592-023-02014-7 · Cited by 514 · see citing works
Self-citationLan, Y., Zhang, D., Xu, C., Hance, K. W., Marelli, B., Qi, J., Yu, H., Qin, G., Sircar, A., Hernández, V. M., et al. (2018) · Science Translational Medicine · doi:10.1126/scitranslmed.aan5488 · Cited by 494 · see citing works
The functional landscape of the human phosphoproteome
Ochoa, D., Jarnuczak, A. F., Viéitez, C., Gehre, M., Soucheray, M., Mateus, A., Kleefeldt, A. A., Hill, A., Garcia-Alonso, L., Stein, F., et al. (2020) · Nature Biotechnology · doi:10.1038/s41587-019-0344-3 · Cited by 491 · see citing works
Molecular Pathways of Colon Inflammation Induced by Cancer Immunotherapy
Luoma, A. M., Suo, S., Williams, H. L., Sharova, T., Sullivan, K., Manos, M., Bowling, P., Hodi, F. S., Rahma, O., Sullivan, R. J., et al. (2020) · Cell · doi:10.1016/j.cell.2020.06.001 · Cited by 484 · see citing works
Gene regulatory network inference in the era of single-cell multi-omics
Badia-i-Mompel, P., Wessels, L., Müller‐Dott, S., Trimbour, R., Flores, R. O. R., Argelaguet, R., & Sáez-Rodríguez, J. (2023) · Nature Reviews Genetics · doi:10.1038/s41576-023-00618-5 · Cited by 475 · see citing works
Kurppa, K. J., Liu, Y., To, C., Zhang, T., Fan, M., Vajdi, A., Knelson, E. H., Xie, Y., Lim, K., Cejas, P., et al. (2020) · Cancer Cell · doi:10.1016/j.ccell.2019.12.006 · Cited by 475 · see citing works
Elhassan, Y. S., Kluckova, K., Fletcher, R. S., Schmidt, M. S., Garten, A., Doig, C. L., Cartwright, D. M., Oakey, L., Burley, C. V., Jenkinson, N., et al. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.07.043 · Cited by 448 · see citing works
WRN helicase is a synthetic lethal target in microsatellite unstable cancers
Chan, E. M., Shibue, T., McFarland, J. M., Gaeta, B., Ghandi, M., Dumont, N., Gonzalez, A., McPartlan, J. S., Li, T., Zhang, Y., et al. (2019) · Nature · doi:10.1038/s41586-019-1102-x · Cited by 458 · see citing works
Self-citationTumor-suppressor genes that escape from X-inactivation contribute to cancer sex bias
Dunford, A. J., Weinstock, D. M., Savova, V., Schumacher, S. E., Cleary, J. P., Yoda, A., Sullivan, T. J., Hess, J. M., Gimelbrant, A. A., Beroukhim, R., et al. (2016) · Nature Genetics · doi:10.1038/ng.3726 · Cited by 459 · see citing works
Turner, N. C., Liu, Y., Zhu, Z., Loi, S., Colleoni, M. A., Loibl, S., DeMichele, A. M., Harbeck, N., André, F., Bayar, M. A., et al. (2019) · Journal of Clinical Oncology · doi:10.1200/jco.18.00925 · Cited by 454 · see citing works
Spatially confined sub-tumor microenvironments in pancreatic cancer
Grünwald, B. T., Devisme, A., Andrieux, G., Vyas, F., Aliar, K., McCloskey, C. W., Macklin, A., Jang, G. H., Denroche, R., Romero, J. M., et al. (2021) · Cell · doi:10.1016/j.cell.2021.09.022 · Cited by 433 · see citing works
Hwang, W. L., Jagadeesh, K. A., Guo, J. A., Hoffman, H. I., Yadollahpour, P., Reeves, J. W., Mohan, R., Drokhlyansky, E., Van Wittenberghe, N., Ashenberg, O., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01134-8 · Cited by 426 · see citing works
Neutrophil profiling illuminates anti-tumor antigen-presenting potency
Wu, Y. C., Ma, J., Yang, X., Fang, N., Zhang, T., Ji, S., Rao, D., Feng, H., Gao, K., Gu, X., et al. (2024) · Cell · doi:10.1016/j.cell.2024.02.005 · Cited by 441 · see citing works
- Authors
- Liberzon, A., Birger, C., Thorvaldsdóttir, H., Ghandi, M., Mesirov, J. P., & Tamayo, P.
- Affiliations
- Broad Institute (US)
- Corresponding author
- Mesirov, Jill P.
- Tamayo, Pablo
- Venue
- Cell Systems
- Publisher
- Elsevier BV
- Published
- 2015-12
- Volume
- 1
- Issue
- 6
- Pages
- 417-425
- ISSN
- 2405-4712 (ISSN-L)
- PMC
- PMC4707969
- OpenAlex
- W2214074259
- Cited by
- 13,807
- References
- 37
- Citations by year
- 2026: 2174 · 2025: 2294 · 2024: 2415 · 2023: 1982 · 2022: 1708 · 2021: 1298 · 2020: 926 · 2019: 534 · 2018: 270 · 2017: 154 · 2016: 44 · 2013: 3
- FWCI
- 68.21
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cell Systems (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- National Institutes of Health
- National Cancer Institute (R01CA154480, U54CA112962, R01CA121941)
- National Institute of General Medical Sciences (R01GM074024)
- 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
- Hallmark gene sets, gene set enrichment analysis, biological processes, cancer hallmarks
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
