The DOI matches its Crossref record; 37 of the 37 references it cites were found in a registry or an index.
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.
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“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
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“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]
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“( 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]
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“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]
Experimental — accuracy not yet measuredIn the citing paper
“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 Enterococcus peptidoglycan remodeling promotes checkpoint inhibitor cancer immunotherapy (2021) · cites this paper as [33]
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Self-citationThe basics of epithelial-mesenchymal transition
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The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity
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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
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
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Genetic effects on gene expression across human tissues
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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
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
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Abudayyeh, O. O., Gootenberg, J. S., Konermann, S., Joung, J., Slaymaker, I. M., Cox, D. B. T., Shmakov, S., Makarova, K. S., Semenova, E., Minakhin, L., et al. (2016) · Science · doi:10.1126/science.aaf5573 · Cited by 2,336
Metadata
- 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
- 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
- Health Sciences › Medicine › Health Informatics › 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
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