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Molecular signatures database (MSigDB) 3.0
Open accessAbstract
MOTIVATION: Well-annotated gene sets representing the universe of the biological processes are critical for meaningful and insightful interpretation of large-scale genomic data. The Molecular Signatures Database (MSigDB) is one of the most widely used repositories of such sets. RESULTS: We report the availability of a new version of the database, MSigDB 3.0, with over 6700 gene sets, a complete revision of the collection of canonical pathways and experimental signatures from publications, enhanced annotations and upgrades to the web site. AVAILABILITY AND IMPLEMENTATION: MSigDB is freely available for non-commercial use at http://www.broadinstitute.org/msigdb.
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“Transcription factor activities can be estimated using enrichment of their downstream targets26,27.”
From Positive selection of somatically mutated clones identifies adaptive pathways in metabolic liver disease (2023) · cites this paper as [27]
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“Ground truth is annotated according to Ensembl Release 110 [13], as collected in the MSigDB [29] C1 gene set (c1.all.v2023.2.Hs.symbols.gmt).”
From LAB-Bench: Measuring Capabilities of Language Models for Biology Research (2024) · cites this paper as [29]
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“Since transcription factor gene expression levels do not always reflect their functional importance, we chose those with the highest or lowest activities based on the induction or suppression of their downstream targets (See methods for details)26,27.”
From Positive selection of somatically mutated clones identifies adaptive pathways in metabolic liver disease (2023) · cites this paper as [27]
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“which has a clear relationship to the diet phenotype”
From RERconverge Expansion: Using Relative Evolutionary Rates to Study Complex Categorical Trait Evolution (2024) · cites this paper as Liberzon et al. 2011
Experimental — accuracy not yet measuredIn the citing paper
“The limma authors maintain mouse and human versions of the Molecular Signatures Database collections (64) in R binary format that can be conveniently used with camera, mroast or romer”
From limma powers differential expression analyses for RNA-sequencing and microarray studies (2015) · cites this paper as [64]
In the citing paper
“This OXTR/CD38 module was also enriched in genesets reported in the Molecular Signatures Database34 that are associated with several behavioral and cognitive state processes including feeding behavior (p = 5.83 × 10−3), cognition (p = 7.44 × 10−3), and behavioral response to stimuli (p = 1.05 × 10−2).”
From Oxytocin pathway gene networks in the human brain (2019) · cites this paper as [34]
In the citing paper
“Biological process labels are stored in databases such as MSigDB (Liberzon et al, 2011), the Gene Ontology (Ashburner et al, 2000; The Gene Ontology Consortium, 2017), or the pathway databases KEGG (Kanehisa et al, 2017) and Reactome (Fabregat et al, 2018).”
From Current best practices in single-cell RNA-seq analysis: a tutorial (2019) · cites this paper as Liberzon et al, 2011
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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
Self-citationGene Ontology: tool for the unification of biology
Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T., et al. (2000) · Nature Genetics · doi:10.1038/75556 · Cited by 43,206
KEGG: Kyoto Encyclopedia of Genes and Genomes
Kanehisa, M. (2000) · Nucleic Acids Research · doi:10.1093/nar/28.1.27 · Cited by 37,077
KEGG: Kyoto Encyclopedia of Genes and Genomes
Ogata, H., Goto, S., Sato, K., Fujibuchi, W., Bono, H., & Kanehisa, M. (1999) · Nucleic Acids Research · doi:10.1093/nar/27.1.29 · Cited by 31,232
Huang, D. W., Sherman, B. T., & Lempicki, R. A. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkn923 · Cited by 14,108
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
Self-citationTRANSFAC(R) and its module TRANSCompel(R): transcriptional gene regulation in eukaryotes
Matys, V. (2005) · Nucleic Acids Research · doi:10.1093/nar/gkj143 · Cited by 2,142
NCBI GEO: archive for high-throughput functional genomic data
Barrett, T., Troup, D. B., Wilhite, S. E., Ledoux, P., Rudnev, D., Evangelista, C., Kim, I. F., Soboleva, A., Tomashevsky, M., Marshall, K. A., et al. (2008) · Nucleic Acids Research · doi:10.1093/nar/gkn764 · Cited by 1,043
Reactome knowledgebase of human biological pathways and processes
Matthews, L., Gopinath, G., Gillespie, M., Caudy, M., Croft, D., de Bono, B., Garapati, P., Hemish, J., Hermjakob, H., Jassal, B., et al. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkn863 · Cited by 873
Parkinson, H., Kapushesky, M., Kolesnikov, N. N., Rustici, G., Shojatalab, M., Abeygunawardena, N., Bérubé, H., Dyląg, M., Emam, I., Farne, A., et al. (2008) · Nucleic Acids Research · doi:10.1093/nar/gkn889 · Cited by 418
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Qian, J., Shao, X., Bao, H., Yin, F., Guo, W., Li, C., Li, A., Hua, H., & Fan, X. (2025) · Nature Communications · doi:10.1038/s41467-025-57029-9 · Cited by 62
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Georgakilas, G. K., Vlachos, I. S., Zagganas, K., Vergoulis, T., Paraskevopoulou, M. D., Kanellos, I., Tsanakas, P. D., Dellis, D., Fevgas, A., Dalamagas, T., et al. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv1254 · Cited by 59
Geraniol suppresses prostate cancer growth through down‐regulation of E2F8
Lee, S., Park, Y. R., Kim, S., Park, E., Kang, M. J., So, I., Chun, J. N., & Jeon, J. (2016) · Cancer Medicine · doi:10.1002/cam4.864 · Cited by 59
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Doty, R. T., Yan, X. S., Lausted, C. G., Munday, A. D., Yang, Z., Yi, D., Jabbari, N., Liu, L., Keel, S., Tian, Q., et al. (2018) · Blood · doi:10.1182/blood-2018-05-850412 · Cited by 59
Zaro, B. W., Noh, J. J., Mascetti, V. L., Demeter, J., George, B. M., Żukowska, M., Gulati, G. S., Sinha, R., Flynn, R. A., Banuelos, A. M., et al. (2020) · eLife · doi:10.7554/elife.62210 · Cited by 59
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Pikman, Y., Ocasio-Martinez, N., Alexe, G., Dimitrov, B., Kitara, S., Diehl, F. F., Robichaud, A. L., Conway, A. S., Ross, L. S., Su, A. H., et al. (2021) · Leukemia · doi:10.1038/s41375-021-01361-8 · Cited by 59
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Rabanal‐Ruiz, Y., Byron, A., Wirth, A., Madsen, R. R., Sedlackova, L., Hewitt, G., Nelson, G., Stingele, J., Wills, J. C., Zhang, T., et al. (2021) · The Journal of Cell Biology · doi:10.1083/jcb.202004010 · Cited by 58
Pellegrinelli, V., Rodríguez‐Cuenca, S., Rouault, C., Figueroa‐Juárez, E., Schilbert, H. M., Virtue, S., Moreno‐Navarrete, J. M., Bidault, G., Vazquez-Borrego, M. C., Dias, A. R., et al. (2022) · Nature Metabolism · doi:10.1038/s42255-022-00561-5 · Cited by 58
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Campbell, T. M., Liu, Z., Zhang, Q., Moncada‐Vélez, M., Covill, L., Zhang, P., Darazam, I. A., Bastard, P., Bizien, L., Bucciol, G., et al. (2022) · The Journal of Experimental Medicine · doi:10.1084/jem.20220202 · Cited by 58
Yu, Y., Li, Y., Zhou, L., Cheng, X., & Gong, Z. (2024) · Cancer Letters · doi:10.1016/j.canlet.2024.217243 · Cited by 59
Zhang, Y.-P., Guo, Z.-Q., Cai, X.-T., Rong, Z.-X., Fang, Y., Chen, J., Zhuang, K., Ruan, M.-J., Ma, S.-C., Lin, L.-Y., et al. (2025) · Cancer Cell · doi:10.1016/j.ccell.2025.02.024 · Cited by 58
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Yadetie, F., Zhang, X., Hanna, E. M., Aranguren-Abadía, L., Eide, M., Blaser, N., Brun, M., Jonassen, I., Goksøyr, A., & Karlsen, O. A. (2018) · Aquatic Toxicology · doi:10.1016/j.aquatox.2018.06.003 · Cited by 58
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Higa, K. C., Goodspeed, A., Chavez, J. S., De Dominici, M., Danis, E., Zaberezhnyy, V., Rabe, J. L., Tenen, D. G., Pietras, E. M., & DeGregori, J. (2021) · Journal of Experimental Medicine · doi:10.1084/jem.20200560 · Cited by 57
Wu, I., Zeng, A., Greer-Short, A., Aycinena, J. A., Tefera, A. E., Shenwai, R., Farshidfar, F., Van Pell, M., Xu, E., Reid, C., et al. (2024) · Communications Medicine · doi:10.1038/s43856-024-00450-w · Cited by 57
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Yuan, J., Xie, A., Cao, Q., Li, X., & Chen, J. (2020) · BioMed Research International · doi:10.1155/2020/6909672 · Cited by 57
Wang, Z., Wang, C., Lin, S., & Yu, X. (2021) · Frontiers in Oncology · doi:10.3389/fonc.2021.725292 · Cited by 57
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Boix, O., Martinez, M., Vidal, S., Giménez-Alejandre, M., Palenzuela, L., Lorenzo-Sanz, L., Quevedo, L., Moscoso, O., Ruiz‐Orera, J., Ximénez‐Embún, P., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-34529-6 · Cited by 57
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Lovegrove, C. E., Bešević, J., Wiberg, A., Lacey, B., Littlejohns, T. J., Allen, N. E., Goldsworthy, M. E., Kim, J., Hannan, F. M., Curhan, G. C., et al. (2023) · Journal of the American Society of Nephrology · doi:10.1681/asn.0000000000000238 · Cited by 57
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Kim, J., Ghasemzadeh, N., Eapen, D. J., Chung, N. C., Storey, J. D., Quyyumi, A. A., & Gibson, G. C. (2014) · Genome Medicine · doi:10.1186/gm560 · Cited by 57
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Olson, B. G., Zhu, X., Norgard, M. A., Diba, P., Levasseur, P. R., Buenafe, A. C., Huisman, C., Burfeind, K. G., Michaelis, K. A., Kong, G., et al. (2021) · Brain Behavior and Immunity · doi:10.1016/j.bbi.2021.07.002 · Cited by 56
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Conley, A. B., Minciacchi, V. R., Lee, D. H., Knudsen, B. S., Karlan, B. Y., Citrigno, L., Viglietto, G., Tewari, M., Freeman, M. R., Demichelis, F., et al. (2016) · RNA Biology · doi:10.1080/15476286.2016.1259061 · Cited by 56
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van Buuren, N. J., Ramírez, R., Turner, S., Chen, D. A., Suri, V., Aggarwal, A., Moon, C., Kim, S., Kornyeyev, D., Bui, N., et al. (2021) · JHEP Reports · doi:10.1016/j.jhepr.2021.100388 · Cited by 55
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Alvarez-Breckenridge, C. A., Markson, S. C., Stocking, J. H., Nayyar, N., Lastrapes, M., Strickland, M. R., Kim, A. E., de Sauvage, M. A., Dahal, A., Larson, J. M., et al. (2022) · Cancer Immunology Research · doi:10.1158/2326-6066.cir-21-0870 · Cited by 55
Technology meets TILs: Deciphering T cell function in the -omics era
Hudson, W. H., & Wieland, A. (2022) · Cancer Cell · doi:10.1016/j.ccell.2022.09.011 · Cited by 55
Yuan, Q., Zhang, W., & Shang, W. (2022) · Frontiers in Endocrinology · doi:10.3389/fendo.2022.1045167 · Cited by 55
Dondi, A., Lischetti, U., Jacob, F., Singer, F., Borgsmüller, N., Coelho, R., Aebersold, R. H., Ak, M., Alquaddoomi, F., Albert, S. I., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-43387-9 · Cited by 55
Barišić, D., Chin, C. R., Meydan, C., Teater, M. R., Tsialta, I., Mlynarczyk, C., Chadburn, A., Wang, X., Sarkozy, M., Xia, M., et al. (2024) · Cancer Cell · doi:10.1016/j.ccell.2024.02.010 · Cited by 55
Sharma, G., Sharma, A., Kim, I., Gon, D., Kim, S., Park, E. S., Noh, J. G., Lee, J.-H., Ku, J. H., Choi, Y. H., et al. (2024) · Nature Immunology · doi:10.1038/s41590-024-01816-x · Cited by 58
Zhou, X., Zhang, L., Aryal, S., Veasey, V., Tajik, A., Restelli, C., Moreira, S., Zhang, P., Zhang, Y., Hope, K. J., et al. (2024) · Blood · doi:10.1182/blood.2023023644 · Cited by 55
Interpretable spatially aware dimension reduction of spatial transcriptomics with STAMP
Zhong, C., Ang, K. S., & Chen, J. (2024) · Nature Methods · doi:10.1038/s41592-024-02463-8 · Cited by 60
Kang, T. H., Park, Y., Bader, J. S., & Friedmann, T. (2013) · PLoS ONE · doi:10.1371/journal.pone.0074967 · Cited by 55
Lisowska, K. M., Olbryt, M., Student, S., Kujawa, K. A., Cortez, A. J., Simek, K., Dansonka‐Mieszkowska, A., Rzepecka, I. K., Tudrej, P., & Kupryjańczyk, J. (2016) · Journal of Cancer Research and Clinical Oncology · doi:10.1007/s00432-016-2147-y · Cited by 55
Kogel, U., Titz, B., Schlage, W. K., Nury, C., Martin, F. P., Oviedo, A., Lebrun, S., Elamin, A., Guedj, E., Trivedi, K., et al. (2016) · Regulatory Toxicology and Pharmacology · doi:10.1016/j.yrtph.2016.11.001 · Cited by 55
Jadamba, E., & Shin, M. (2016) · BioMed Research International · doi:10.1155/2016/7147039 · Cited by 55
Common Features of Regulatory T Cell Specialization During Th1 Responses
Lambert, K., Moresi, C., Rakebrandt, N., Zhou, X., Schorer, M., Dolowschiak, T., Kirchner, F., Rost, F., Keller, C. W., McHugh, D., et al. (2018) · Frontiers in Immunology · doi:10.3389/fimmu.2018.01344 · Cited by 55
Genes with High Network Connectivity Are Enriched for Disease Heritability
Kim, S. S., Dai, C. L., Hormozdiari, F., van de Geijn, B., Gazal, S., Park, Y., O’Connor, L. J., Amariuta, T., Loh, P., Finucane, H. K., et al. (2019) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2019.03.020 · Cited by 55
CINSARC signature as a prognostic marker for clinical outcome in sarcomas and beyond
Chibon, F., Lesluyes, T., Valentin, T., & Guellec, S. L. (2018) · Genes Chromosomes and Cancer · doi:10.1002/gcc.22703 · Cited by 55
Alshabi, A. M., Vastrad, B. M., Shaikh, I. A., & Vastrad, C. M. (2019) · Biomolecules · doi:10.3390/biom9050201 · Cited by 56
In silico drug repositioning: from large-scale transcriptome data to therapeutics
Kwon, O., Kim, W., Cha, H., & Lee, H. (2019) · Archives of Pharmacal Research · doi:10.1007/s12272-019-01176-3 · Cited by 55
D’Antonio‐Chronowska, A., Donovan, M. K. R., Greenwald, W. W. Y., Nguyen, J., Fujita, K., Hashem, S. I., Matsui, H., Soncin, F., Parast, M. M., Ward, M. C., et al. (2019) · Stem Cell Reports · doi:10.1016/j.stemcr.2019.09.011 · Cited by 55
Kohmoto, T., Masuda, K., Shoda, K., Takahashi, R., Ujiro, S., Tange, S., Ichikawa, D., Otsuji, E., & Imoto, I. (2019) · Gastric Cancer · doi:10.1007/s10120-019-01014-x · Cited by 55
Szostak, J., Wong, E. T., Titz, B., Lee, T., Wong, S. K., Low, T., Lee, K. M., Zhang, J., Kumar, A., Schlage, W. K., et al. (2020) · American Journal of Physiology-Heart and Circulatory Physiology · doi:10.1152/ajpheart.00613.2019 · Cited by 55
Dynamic transcriptional reprogramming leads to immunotherapeutic vulnerabilities in myeloma
Frede, J., Anand, P., Sotudeh, N., Pinto, R. A., Nair, M. S., Stuart, H., Yee, A. J., Vijaykumar, T., Waldschmidt, J. M., Potdar, S. V., et al. (2021) · Nature Cell Biology · doi:10.1038/s41556-021-00766-y · Cited by 55
Joshi, M., Kim, J., D’Alessandro, A., Monk, E., Bruce, K., Elajaili, H., Nozik-Grayck, E., Goodspeed, A., Costello, J. C., & Schlaepfer, I. R. (2020) · Cancers · doi:10.3390/cancers12113431 · Cited by 54
Galanina, N., Bejar, R. L., Choi, M. Y., Goodman, A. M., Wieduwilt, M. J., Mulroney, C. M., Kim, L., Yeerna, H., Tamayo, P., Vergilio, J., et al. (2018) · Cancers · doi:10.3390/cancers11010011 · Cited by 54
Self-citationEmergence and maintenance of actionable genetic drivers at medulloblastoma relapse
Richardson, S., Hill, R. M., Kui, C., Lindsey, J. C., Grabovksa, Y., Keeling, C., Pease, L. I., Bashton, M., Crosier, S., Vinci, M., et al. (2021) · Neuro-Oncology · doi:10.1093/neuonc/noab178 · Cited by 54
Asosingh, K., COMHAIR, S. A. A., Mavrakis, L. A., Xu, W., Horton, D., Taylor, I., Tkachenko, S., Hu, B., & ERZURUM, S. C. (2021) · Scientific Reports · doi:10.1038/s41598-021-94163-y · Cited by 54
Majd, H., Amin, S., Ghazizadeh, Z., Cesiulis, A., Arroyo, E. J., Lankford, K. L., Majd, A., Farahvashi, S., Chemel, A. K., Okoye, M., et al. (2023) · Cell stem cell · doi:10.1016/j.stem.2023.04.006 · Cited by 54
Wang, P., Kljavin, N. M., Nguyen, T. T. T., Storm, E. E., Marsh, B., Jiang, J. W., Lin, W., Menon, H., Piskol, R., & de Sauvage, F. J. (2023) · Cell stem cell · doi:10.1016/j.stem.2023.07.013 · Cited by 55
Decoding complex patterns of genomic rearrangement in hepatocellular carcinoma
Fernandez-Banet, J., Lee, N. P. Y., Chan, K., Gao, H., Liu, X., Sung, W.-K. K., Tan, W., Fan, S. T., Poon, R. T. P., Li, S., et al. (2014) · Genomics · doi:10.1016/j.ygeno.2014.01.003 · Cited by 54
Liu, N. Q., Dekker, L. J. M., Stingl, C., Güzel, C., Marchi, T. D., Martens, J. W. M., Foekens, J. A., Luider, T. M., & Umar, A. (2013) · Journal of Proteome Research · doi:10.1021/pr4005794 · Cited by 55
Large-scale microarray profiling reveals four stages of immune escape in non-Hodgkin lymphomas
Tosolini, M., Algans, C., Pont, F., Ycart, B., & Fournié, J. (2016) · OncoImmunology · doi:10.1080/2162402x.2016.1188246 · Cited by 54
Wen, W. X., Soo, J. S.-S., Kwan, P. Y., Hong, E., Khang, T. F., Mariapun, S., Lee, C. S. M., Hasan, S. N., Rajadurai, P., Yip, C. H., et al. (2016) · Breast Cancer Research · doi:10.1186/s13058-016-0717-1 · Cited by 54
The Pathway Coexpression Network: Revealing pathway relationships
Pita-Juárez, Y. H., Altschuler, G. M., Kariotis, S., Wei, W., Koler, K., Green, C., Tanzi, R. E., & Hide, W. (2018) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006042 · Cited by 54
GSAE: an autoencoder with embedded gene-set nodes for genomics functional characterization
Chen, H.-I. H., Chiu, Y., Zhang, T., Zhang, S., Huang, Y., & Chen, Y. (2018) · BMC Systems Biology · doi:10.1186/s12918-018-0642-2 · Cited by 54
Defining the genetic control of human blood plasma N-glycome using genome-wide association study
Sharapov, S., Tsepilov, Y. A., Klarić, L., Mangino, M., Thareja, G., Shadrina, A. S., Šimurina, M., Dagostino, C., Dmitrieva, J., Vilaj, M. Ć., et al. (2019) · Human Molecular Genetics · doi:10.1093/hmg/ddz054 · Cited by 54
Optimized CRISPR-mediated gene knockin reveals FOXP3-independent maintenance of human Treg identity
Lam, A. J., Lin, D. T. S., Gillies, J. K., Uday, P., Pesenacker, A. M., Kobor, M. S., & Levings, M. K. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.109494 · Cited by 52
Lanz, T. A., Guilmette, E., Gosink, M. M., Fischer, J. E., Fitzgerald, L. W., Stephenson, D. T., & Pletcher, M. T. (2013) · Molecular Autism · doi:10.1186/2040-2392-4-45 · Cited by 52
Choi, J., Lee, K., Ingvarsdottir, K., Bonasio, R., Saraf, A., Florens, L., Washburn, M. P., Tadros, S., Green, M. R., & Busino, L. (2018) · Nature Cell Biology · doi:10.1038/s41556-018-0084-5 · Cited by 50
Metadata
- Authors
- Liberzon, A., Subramanian, A., Pinchback, R., Thorvaldsdóttir, H., Tamayo, P., & Mesirov, J. P.
- Affiliations
- Broad Institute (US)
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2011-05-05
- Volume
- 27
- Issue
- 12
- Pages
- 1739-1740
- ISSN
- 1367-4803 (ISSN-L)
- 1367-4811
- PMC
- PMC3106198
- OpenAlex
- W2010457001
- Cited by
- 7,111
- References
- 14
- Citations by year
- 2026: 675 · 2025: 1003 · 2024: 1086 · 2023: 942 · 2022: 825 · 2021: 774 · 2020: 602 · 2019: 374 · 2018: 203 · 2017: 151 · 2016: 141 · 2015: 117 · 2014: 102 · 2013: 64 · 2012: 38
- FWCI
- 27.81
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Bioinformatics (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- HighWire Press Open Archive (submittedVersion)
- Funders
- National Cancer Institute (R01CA121941)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Health Sciences › Medicine › Health Informatics › Biomedical Text Mining and Ontologies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- MSigDB, gene sets, canonical pathways, experimental signatures, gene set annotation, biological process annotation, genomic data interpretation, molecular signatures
- MeSH terms
- Internet, Genomics, Databases, Genetic, Molecular Sequence Annotation
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