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Enrichment Map: A Network-Based Method for Gene-Set Enrichment Visualization and Interpretation
Open accessAbstract
BACKGROUND: Gene-set enrichment analysis is a useful technique to help functionally characterize large gene lists, such as the results of gene expression experiments. This technique finds functionally coherent gene-sets, such as pathways, that are statistically over-represented in a given gene list. Ideally, the number of resulting sets is smaller than the number of genes in the list, thus simplifying interpretation. However, the increasing number and redundancy of gene-sets used by many current enrichment analysis software works against this ideal. PRINCIPAL FINDINGS: To overcome gene-set redundancy and help in the interpretation of large gene lists, we developed "Enrichment Map", a network-based visualization method for gene-set enrichment results. Gene-sets are organized in a network, where each set is a node and edges represent gene overlap between sets. Automated network layout groups related gene-sets into network clusters, enabling the user to quickly identify the major enriched functional themes and more easily interpret the enrichment results. CONCLUSIONS: Enrichment Map is a significant advance in the interpretation of enrichment analysis. Any research project that generates a list of genes can take advantage of this visualization framework. Enrichment Map is implemented as a freely available and user friendly plug-in for the Cytoscape network visualization software (http://baderlab.org/Software/EnrichmentMap/).
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“Furthermore, gene set enrichment analysis (GSEA) revealed that the hypoxia pathway is impaired in miR-140G/G, but not in miR-140−/− chondrocytes”
From Gain-of-function mutation of microRNA-140 in human skeletal dysplasia (2019) · cites this paper as [26]
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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
Gene 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
Systematic 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
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
Bioconductor: open software development for computational biology and bioinformatics
Gentleman, R. C., Carey, V. J., Bates, D. M., Bolstad, B., Dettling, M., Dudoit, S., Ellis, B., Gautier, L., Ge, Y., Gentry, J., et al. (2004) · Genome biology · doi:10.1186/gb-2004-5-10-r80 · Cited by 12,082
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
Bindea, G., Mlecnik, B., Hackl, H., Charoentong, P., Tosolini, M., Kirilovsky, A., Fridman, W.-H., Pagès, F., Trajanoski, Z., & Galon, J. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp101 · Cited by 6,280
Maere, S., Heymans, K., & Kuiper, M. T. R. (2005) · Computer applications in the biosciences · doi:10.1093/bioinformatics/bti551 · Cited by 4,093
On the Interpretation of χ 2 from Contingency Tables, and the Calculation of P
Fisher, R. A. (1922) · Journal Of The Royal Statistical Society · doi:10.2307/2340521 · Cited by 2,975
Research works printed but not linked: 1
- S Draghici, 2003, Global functional profiling of gene expression., Genomics, 81, 98
Cited by
Sorted by citations
Items 701–800 of 1,005
categoryCompare, an analytical tool based on feature annotations
Flight, R. M., Harrison, B. J., Mohammad, F., Bunge, M. B., Moon, L. D. F., Petruska, J. C., & Rouchka, E. C. (2014) · Frontiers in Genetics · doi:10.3389/fgene.2014.00098 · Cited by 33
Encoding of Contextual Fear Memory Requires De Novo Proteins in the Prelimbic Cortex
Rizzo, V., Touzani, K., Raveendra, B., Swarnkar, S., Lora, J. C., Kadakkuzha, B. M., Liu, X.-A., Zhang, C., Betel, D., Stackman, R. W., et al. (2016) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2016.10.002 · Cited by 38
Madecassic Acid Derivatives as Potential Anticancer Agents: Synthesis and Cytotoxic Evaluation
Valdeira, A. S. C., Darvishi, E., Woldemichael, G. M., Beutler, J. A., Gustafson, K. R., & Salvador, J. A. R. (2019) · Journal of Natural Products · doi:10.1021/acs.jnatprod.8b00864 · Cited by 33
Phf6-null hematopoietic stem cells have enhanced self-renewal capacity and oncogenic potentials
Hsu, Y.-C., Chen, T., Lin, C., Yuan, C., Hsu, C., Hou, H., Kao, C., Chuang, P., Chen, Y.-R., Chou, W., et al. (2019) · Blood Advances · doi:10.1182/bloodadvances.2019000391 · Cited by 33
Revealing Dynamic Protein Acetylation across Subcellular Compartments
Baeza, J., Lawton, A. J., Fan, J., Smallegan, M. J., Lienert, I., Gandhi, T., Bernhardt, O. M., Reiter, L., & Denu, J. M. (2020) · Journal of Proteome Research · doi:10.1021/acs.jproteome.0c00088 · Cited by 33
Pennemann, F. L., Mussabekova, A., Urban, C., Stukalov, A., Andersen, L. L., Grass, V., Lavacca, T. M., Holze, C., Oubraham, L., Benamrouche, Y., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-27192-w · Cited by 36
Babunovic, G. H., DeJesus, M. A., Bosch, B., Chase, M. R., Barbier, T., Dickey, A. K., Bryson, B. D., Rock, J. M., & Fortune, S. M. (2022) · mBio · doi:10.1128/mbio.03683-21 · Cited by 34
Rao, C., Shi, H., Zhou, C., Zhu, D., Zhao, M., Wang, Z., Yang, Y., Chen, J., Liao, L., Tang, J., et al. (2016) · Neurochemical Research · doi:10.1007/s11064-016-1957-2 · Cited by 33
Basso, V., Znaidi, S., Lagage, V., Cabral, V., Schönherr, F. A., LeibundGut‐Landmann, S., d’Enfert, C., & Bachellier‐Bassi, S. (2017) · Molecular Microbiology · doi:10.1111/mmi.13758 · Cited by 36
Zhao, C., Zou, H., Zhang, J., Wang, J., & Liu, H. (2018) · Oncology Reports · doi:10.3892/or.2018.6702 · Cited by 33
Wong, C., & Venkatachalam, K. (2019) · Human Molecular Genetics · doi:10.1093/hmg/ddz104 · Cited by 34
Sex-specific cell types and molecular pathways indicate fibro-calcific aortic valve stenosis
Myasoedova, V. A., Massaiu, I., Moschetta, D., Chiesa, M., Songia, P., Valerio, V., Alfieri, V., Capoulade, R., Trabattoni, D., Andreini, D., et al. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.747714 · Cited by 32
Cai, Y., Pinheiro‐de‐Sousa, I., Slobodyanyuk, M., Chen, F., Huynh, T., Kanyo, J. E., Tang, P., Fuentes, L. A., Braker, A., Welch, R., et al. (2025) · Nature Neuroscience · doi:10.1038/s41593-025-01973-8 · Cited by 34
Derous, D., Mitchell, S. E., Green, C. L., Chen, L., Han, J. J., Wang, Y., Promislow, D., Lusseau, D., Speakman, J. R., & Douglas, A. (2016) · Aging · doi:10.18632/aging.100895 · Cited by 34
Riddell, N., & Crewther, S. G. (2017) · Investigative Ophthalmology & Visual Science · doi:10.1167/iovs.16-20618 · Cited by 32
Rafehi, H., Kaspi, A., Ziemann, M., Okabe, J., Karagiannis, T. C., & El‐Osta, A. (2017) · Epigenetics · doi:10.1080/15592294.2017.1371892 · Cited by 32
Giummarra, L., Crewther, S. G., Riddell, N., Murphy, M., & Crewther, D. P. (2018) · PeerJ · doi:10.7717/peerj.5048 · Cited by 32
Huang, S., Choi, M. H., Huang, H., Wang, X., Chang, Y. C., & Kim, J. Y. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.108394 · Cited by 32
Altenburger, A., Cai, H., Li, Q., Drumm, K., Kim, M., Zhu, Y., Garcia‐Cuetos, L., Zhan, X., Hansen, P. J., John, U., et al. (2020) · The ISME Journal · doi:10.1038/s41396-020-00830-9 · Cited by 32
Epigenetic inactivation of the autophagy–lysosomal system in appendix in Parkinson’s disease
Gordevičius, J., Li, P., Marshall, L. L., Killinger, B. A., Lang, S., Ensink, E., Kuhn, N. C., Cui, W., Maroof, N., Lauria, R., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-25474-x · Cited by 36
Lewis, E. L., Xu, R., Beltra, J., Ngiow, S. F., Cohen, J. B., Telange, R., Crane, A., Sawinski, D. L., Wherry, E. J., & Porrett, P. M. (2021) · The Journal of Experimental Medicine · doi:10.1084/jem.20201599 · Cited by 32
Wightman, D. P., Savage, J. E., Tissink, E., Romero, C., Jansen, I. E., & Posthuma, D. (2023) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2023.03.004 · Cited by 34
Meng, X., Xue, M., Xu, P., Hu, F., Sun, B., & Xiao, Z. (2017) · Genomics · doi:10.1016/j.ygeno.2017.02.003 · Cited by 32
Schaeffer, J., Tannahill, D., Cioni, J.-M., Rowlands, D., & Keynes, R. J. (2018) · Developmental Biology · doi:10.1016/j.ydbio.2018.06.014 · Cited by 32
Transcriptional and metabolic data integration and modeling for identification of active pathways
Jauhiainen, A., Nerman, O., Michailidis, G. C., & Jörnsten, R. J. (2012) · Biostatistics · doi:10.1093/biostatistics/kxs016 · Cited by 31
Alterations in Placental Gene Expression of Pregnant Women with Chronic Chagas Disease
Juiz, N. A., Torrejón, I. R., Burgos, M., Torres, A. M. F., Duffy, T., Cayo, N. M., Tabasco, A., Salvo, M., Longhi, S. A., & Schijman, A. G. (2018) · American Journal Of Pathology · doi:10.1016/j.ajpath.2018.02.011 · Cited by 31
Lobo, I. K. C., do Nascimento, Á. R., Yamagishi, M. E. B., Guiguen, Y., da Silva, G. F., Séverac, D., Amaral, A. D. C., Reis, V. R., & de Almeida, F. L. (2020) · Genomics · doi:10.1016/j.ygeno.2020.01.022 · Cited by 31
NASA GeneLab Platform Utilized for Biological Response to Space Radiation in Animal Models
McDonald, J. T., Stainforth, R., Miller, J., Cahill, T., da Silveira, W. A., Rathi, K. S., Hardiman, G., Taylor, D. M., Costes, S. V., Chauhan, V., et al. (2020) · Cancers · doi:10.3390/cancers12020381 · Cited by 31
Weinguny, M., Klanert, G., Eisenhut, P., Jonsson, A., Ivansson, D., Lövgren, A., & Borth, N. (2020) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2020.05.020 · Cited by 31
Groot, C., Grothe, M. J., Mukherjee, S., Jelistratova, I., Jansen, I. E., van Loenhoud, A. C., Risacher, S. L., Saykin, A. J., Donald, C. L. M., Mez, J., et al. (2021) · NeuroImage Clinical · doi:10.1016/j.nicl.2021.102660 · Cited by 31
POGZ promotes homology‐directed DNA repair in an HP1‐dependent manner
Heath, J., Simo‐Cheyou, E. R., Findlay, S., Luo, V. M., Carpio, E. P., Lee, J., Djerir, B., Chen, X., Morin, T., Lebeau, B., et al. (2021) · EMBO Reports · doi:10.15252/embr.202051041 · Cited by 33
UPRmt activation improves pathological alterations in cellular models of mitochondrial diseases
Suarez-Rivero, J. M., Pastor‐Maldonado, C. J., Povea-Cabello, S., Álvarez-Córdoba, M., Villalón-García, I., Talaverón-Rey, M., Suárez-Carrillo, A., Munuera-Cabeza, M., Reche-López, D., Cilleros-Holgado, P., et al. (2022) · Orphanet Journal of Rare Diseases · doi:10.1186/s13023-022-02331-8 · Cited by 31
Epidermal Immunity and Function: Origin in Neonatal Skin
Visscher, M. O., Carr, A. N., & Narendran, V. (2022) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2022.894496 · Cited by 32
Candidate genes for mastitis resistance in dairy cattle: a data integration approach
Brajnik, Z., & Ogorevc, J. (2023) · Journal of Animal Science and Biotechnology/Journal of animal science and biotechnology · doi:10.1186/s40104-022-00821-0 · Cited by 31
Dysregulation of Npas2 leads to altered metabolic pathways in a murine knockout model
O’Neil, D. S., Figueroa, H. M., Mistretta, T., Su, C., Lane, R. H., & Aagaard, K. M. (2013) · Molecular Genetics and Metabolism · doi:10.1016/j.ymgme.2013.08.015 · Cited by 32
Karagiannis, G. S., Pavlou, M. P., Saraon, P., Musrap, N., Xie, A., Batruch, I., Prassas, I., Dimitromanolakis, A., Petraki, C. D., & Diamandis, E. P. (2014) · Journal of Proteomics · doi:10.1016/j.jprot.2014.03.018 · Cited by 31
Cross-species proteomics in analysis of mammalian sperm proteins
Bayram, H. L., Claydon, A. J., Brownridge, P., Hurst, J. L., Mileham, A. J., Stockley, P., Beynon, R. J., & Hammond, D. E. (2016) · Journal of Proteomics · doi:10.1016/j.jprot.2015.12.027 · Cited by 33
Kim, K., Kim, M., Adamopoulos, I. E., & Tagkopoulos, I. (2019) · Clinical Immunology · doi:10.1016/j.clim.2019.03.002 · Cited by 31
Modeling methyl-sensitive transcription factor motifs with an expanded epigenetic alphabet
Viner, C., Ishak, C. A., Johnson, J., Walker, N. J., Shi, H., Sjöberg-Herrera, M. K., Shen, S. Y., Lardo, S. M., Adams, D. J., Ferguson-Smith, A. C., et al. (2024) · Genome Biology · doi:10.1186/s13059-023-03070-0 · Cited by 30
A mutation in the viral sensor 2’-5’-oligoadenylate synthetase 2 causes failure of lactation
Oakes, S. R., Gallego‐Ortega, D., Stanford, P. M., Junankar, S. R., Au, W. W. Y., Kikhtyak, Z., von Korff, A., Sergio, C. M., Law, A. M. K., Castillo, L. E., et al. (2017) · PLoS Genetics · doi:10.1371/journal.pgen.1007072 · Cited by 30
Crespo, D., Bogerd, J., Sambroni, É., Gac, F. L., Andersson, E., Edvardsen, R. B., Bergman, E. J., Björnsson, B. T., Taranger, G. L., & Schulz, R. W. (2019) · BMC Genomics · doi:10.1186/s12864-019-5869-9 · Cited by 30
Raimondi, F., Inoue, A., Kadji, F. M. N., Ni, S., González‐Sánchez, J. C., Singh, G., de la Vega, A. A., Sotillo, R., Fischer, B., Aoki, J., et al. (2019) · Oncogene · doi:10.1038/s41388-019-0895-2 · Cited by 30
Liepelt, A., Hohlstein, P., Gussen, H., Xue, J., Aschenbrenner, A. C., Ulas, T., Buendgens, L., Warzecha, K. T., Bartneck, M., Luedde, T., et al. (2020) · Journal of Clinical Medicine · doi:10.3390/jcm9010127 · Cited by 30
Fc receptor-like 4 and 5 define human atypical memory B cells
Li, H., Dement-Brown, J., Liao, P., Mazo, I. A., Mills, F., Kraus, Z., Fitzsimmons, S. P., & Tolnay, M. (2020) · International Immunology · doi:10.1093/intimm/dxaa053 · Cited by 30
Sphingosine kinase 2 restricts T cell immunopathology but permits viral persistence
Studstill, C. J., Pritzl, C. J., Seo, Y., Kim, D. Y., Xia, C., Wolf, J. J., Nistala, R., Vijayan, M., Cho, Y., Kang, K. W., et al. (2020) · Journal of Clinical Investigation · doi:10.1172/jci125297 · Cited by 30
López‐Cortés, A., Guevara‐Ramírez, P., Kyriakidis, N. C., Barba‐Ostria, C., Cáceres, Á. L., Guerrero, S. X., Ortiz‐Prado, E., Munteanu, C. R., Tejera, E., Cevallos-Robalino, D., et al. (2021) · Frontiers in Pharmacology · doi:10.3389/fphar.2021.598925 · Cited by 30
MT1 and MT2 melatonin receptors play opposite roles in brain cancer progression
Kinker, G. S., Ostrowski, L. H., Ribeiro, P. A. C., Chanoch-Myers, R., Muxel, S. M., Tirosh, I., Spadoni, G., Rivara, S., Martins, V. R., Santos, T. G., et al. (2021) · Journal of Molecular Medicine · doi:10.1007/s00109-020-02023-5 · Cited by 31
MMAB promotes negative feedback control of cholesterol homeostasis
Goedeke, L., Canfrán‐Duque, A., Rotllán, N., Chaube, B., Thompson, B. M., Lee, R. G., Cline, G. W., McDonald, J. G., Shulman, G. I., Lasunción, M. A., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-26787-7 · Cited by 32
Therapeutic Targeting of EZH2 and BET BRD4 in Pediatric Rhabdoid Tumors
Ishi, Y., Zhang, Y., Zhang, A., Sasaki, T., Piunti, A., Suri, A., Watanabe, J., Abe, K., He, X., Katagi, H., et al. (2022) · Molecular Cancer Therapeutics · doi:10.1158/1535-7163.mct-21-0646 · Cited by 30
Using protein-per-mRNA differences among human tissues in codon optimization
Hernandez‐Alias, X., Benisty, H., Radusky, L., Serrano, L. G., & Schaefer, M. H. (2023) · Genome biology · doi:10.1186/s13059-023-02868-2 · Cited by 30
Ghate, N. B., Kim, S., Shin, Y., Kim, J., Doche, M. E., Valena, S., Situ, A. J., Kim, S., Rhie, S. K., Lenz, H., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-37883-1 · Cited by 30
Lee, Y., Roh, H., Kim, A., Park, J., Lee, J., Kim, Y.-R., Kang, Y.-R., Kang, H., Kim, S., Kim, H., et al. (2023) · Fish & Shellfish Immunology · doi:10.1016/j.fsi.2023.108844 · Cited by 30
Dormancy within Staphylococcus epidermidis biofilms: a transcriptomic analysis by RNA-seq
Carvalhais, V. M. D., França, Â., Cerca, F., Vitorino, R. M. P., Pier, G. B., Vilanova, M., & Cerca, N. (2014) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-014-5548-3 · Cited by 30
Lobo, N. C., Gedye, C. A., Apostoli, A. J., Brown, K. R., Paterson, J., Stickle, N. H., ROBINETTE, M. A., Fleshner, N. E., Hamilton, R. J., Kulkarni, G. S., et al. (2016) · BMC Cancer · doi:10.1186/s12885-016-2539-z · Cited by 30
Mathä, L., Shim, H. B., Steer, C. A., Yin, Y. H., Martínez-González, I., & Takei, F. (2019) · PLoS ONE · doi:10.1371/journal.pone.0214286 · Cited by 30
A code for transcription elongation speed
Cohen, E., Zafrir, Z., & Tuller, T. (2018) · RNA Biology · doi:10.1080/15476286.2017.1384118 · Cited by 29
Mohseni Ahooyi, T., Shekarabi, M., Torkzaban, B., Langford, T. D., Burdo, T. H., Gordon, J., Datta, P. K., Amini, S., & Khalili, K. (2018) · Scientific Reports · doi:10.1038/s41598-018-34539-9 · Cited by 29
Lay, A. C., Tran, V. D. T., Nair, V., Betin, V. M. S., Hurcombe, J., Barrington, A. F., Pope, R. J. P., Burdet, F., Mehl, F., Kryvokhyzha, D., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-54089-1 · Cited by 31
Zhu, Q., Balasubramanian, A., Asirvatham, J. R., Chatterjee, M., Piyarathna, B., Kaur, J. S., Mohamed, N., Wu, L., Wang, S., Pourfarrokh, N., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-61034-3 · Cited by 30
Rewiring an E3 ligase enhances cold resilience and phosphate use in maize
Liao, H., Zhao, X., Ren, K., Guo, L., Li, Z., Liu, Z., Zhang, X., Su, T., Fu, D., Zhang, Z., et al. (2026) · Nature · doi:10.1038/s41586-026-10142-1 · Cited by 29
Frangou, C. G., Li, Y., Shen, H., Yang, N., Wilson, K. E., Blijlevens, M., Guo, J., Nowak, N. J., & Zhang, J. (2014) · Oncotarget · doi:10.18632/oncotarget.2570 · Cited by 30
Cromar, G. L., Wong, K., Loughran, N. B., On, T., Song, H., Xiong, X., Zhang, Z., & Parkinson, J. (2014) · Genome Biology and Evolution · doi:10.1093/gbe/evu228 · Cited by 29
Systems Proteomics for Translational Network Medicine
Arrell, D. K., & Terzic, A. (2012) · Circulation Cardiovascular Genetics · doi:10.1161/circgenetics.110.958991 · Cited by 29
Wang, S., Liu, J. C., Kim, D., Datti, A., & Zacksenhaus, E. (2016) · Breast Cancer Research · doi:10.1186/s13058-015-0668-y · Cited by 29
Gokhale, A., Hartwig, C. L., Freeman, A. A. H., Das, R., Zlatic, S. A., Vistein, R., Burch, A. M., Carrot, G., Lewis, A. F., Nelms, S., et al. (2016) · Journal of Neuroscience · doi:10.1523/jneurosci.1321-16.2016 · Cited by 29
A Six-LncRNA Expression Signature Associated with Prognosis of Colorectal Cancer Patients
Zhao, J., Xu, J., Shang, A., & Zhang, R. (2018) · Cellular Physiology and Biochemistry · doi:10.1159/000494868 · Cited by 29
Liu, Z., Sun, T., Zhang, Z., Bi, J., & Kong, C. (2020) · Genomics · doi:10.1016/j.ygeno.2020.10.022 · Cited by 29
Brokesh, A. M., Cross, L., Kersey, A. L., Murali, A., Richter, C., Gregory, C. A., Singh, I., & Gaharwar, A. K. (2022) · Science Advances · doi:10.1126/sciadv.abl9404 · Cited by 29
Hsiao, C., Engelenburg, H. J., Jongejan, A., Zhu, J. K., Zhang, B., Mingueneau, M., Moerland, P. D., Huitinga, I., Smolders, J., & Hamann, J. (2022) · iScience · doi:10.1016/j.isci.2022.105785 · Cited by 30
The genetics of niche-specific behavioral tendencies in an adaptive radiation of cichlid fishes
Sommer‐Trembo, C., Santos, M. E., Clark, B., Werner, M., Fages, A., Matschiner, M., Hornung, S., Ronco, F., Oliver, C., Garcia, C., et al. (2024) · Science · doi:10.1126/science.adj9228 · Cited by 31
Saghire, H. E., Vandevoorde, C., Ost, P., Monsieurs, P., Michaux, A., Meerleer, G. D., Baatout, S., & Thierens, H. (2014) · International Journal of Oncology · doi:10.3892/ijo.2014.2260 · Cited by 29
Cassar, P. A., Carpenedo, R. L., Samavarchi‐Tehrani, P., Olsen, J. B., Park, C. J., Chang, W. Y., Chen, Z., Choey, C., Delaney, S. P., Guo, H., et al. (2015) · EMBO Reports · doi:10.15252/embr.201540974 · Cited by 29
Self-citationMcClurg, U. L., Cork, D. M. W., Darby, S., Ryan-Munden, C. A., Nakjang, S., Côrtes, L. M., Treumann, A., Gaughan, L., & Robson, C. N. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw1162 · Cited by 29
Parolo, S., Marchetti, L., Lauria, M., Misselbeck, K., Scott‐Boyer, M., Caberlotto, L., & Priami, C. (2018) · PLoS ONE · doi:10.1371/journal.pone.0194225 · Cited by 30
Graph-based exploitation of gene ontology using GOxploreR for scrutinizing biological significance
Manjang, K., Tripathi, S., Yli-Harja, O. P., Dehmer, M., & Emmert‐Streib, F. (2020) · Scientific Reports · doi:10.1038/s41598-020-73326-3 · Cited by 29
Pentland, D. R., Davis, J., Mühlschlegel, F. A., & Gourlay, C. W. (2021) · npj Biofilms and Microbiomes · doi:10.1038/s41522-021-00238-z · Cited by 28
Ran, X., Zheng, J., Chen, L., Xia, Z., Wang, Y., Sun, C., Guo, C., Lin, P., Liu, F., Wang, C., et al. (2023) · Cancer Immunology Research · doi:10.1158/2326-6066.cir-23-0211 · Cited by 30
Belur, N. R., Bustos, B. I., Lubbe, S. J., & Mazzulli, J. R. (2024) · Neuron · doi:10.1016/j.neuron.2024.05.003 · Cited by 28
Bretz, A. C., Gittler, M. P., Charles, J. P., Gremke, N., Eckhardt, I., Mernberger, M., Mandić, R., Thomale, J., Nist, A., Wanzel, M., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw036 · Cited by 28
Kim, S. M., Rabhi, N., Blum, B. C., Hekman, R. M., Wynne, K. J., Emili, A., Farmer, S. R., & Schlezinger, J. J. (2020) · Archives of Toxicology · doi:10.1007/s00204-020-02815-1 · Cited by 29
Self-citationSemenas, J., Wang, T., Khaja, A. S. S., Mahmud, A. K. M. F., Simoulis, A., Grundström, T., Fällman, M., & Persson, J. L. (2020) · Molecular Oncology · doi:10.1002/1878-0261.12873 · Cited by 28
Newborn infant skin gene expression: Remarkable differences versus adults
Visscher, M. O., Hu, P., Carr, A. N., Bascom, C. C., Isfort, R. J., Creswell, K., Adams, R. L., Tiesman, J. P., Lammers, K., & Narendran, V. (2021) · PLoS ONE · doi:10.1371/journal.pone.0258554 · Cited by 28
Mah, C. Y., Nguyen, A. D. T., Niijima, T., Helm, M., Dehairs, J., Ryan, F. J., Ryan, N. K., Quek, L., Hoy, A. J., Don, A. S., et al. (2024) · British Journal of Cancer · doi:10.1038/s41416-023-02557-8 · Cited by 28
Timmerman, C., Suppiah, S., Gurudatta, B. V., Yang, J., Banerjee, C., Sandstrom, D. J., Corces, V. G., & Sanyal, S. (2013) · Journal of Neuroscience · doi:10.1523/jneurosci.1760-13.2013 · Cited by 29
Topoisomerase IIbeta is required for proper retinal development and survival of postmitotic cells
Li, Y., Hao, H., Tzatzalos, E., Lin, R.-K., Doh, S. T., Liu, L. F., Lyu, Y. L., & Cai, L. (2014) · Biology Open · doi:10.1242/bio.20146767 · Cited by 28
Song, S., Hooiveld, G. J. E. J., Zhang, W., Li, M., Zhao, F., Zhu, J. K., Xu, X., Müller, M. M., Li, C., & Zhou, G. (2016) · Journal of Proteome Research · doi:10.1021/acs.jproteome.5b00922 · Cited by 28
Wang, S., Liu, J. C., Ju, Y., Pellecchia, G., Voisin, V., Wang, D., l, R. L., Ben‐David, Y., Bader, G. D., & Zacksenhaus, E. (2017) · JCI Insight · doi:10.1172/jci.insight.93313 · Cited by 28
Self-citationFukushima, A., Iwasa, M., Nakabayashi, R., Kobayashi, M., Nishizawa, T., Okazaki, Y., Saito, K., & Kusano, M. (2017) · Frontiers in Plant Science · doi:10.3389/fpls.2017.01464 · Cited by 28
Organoids model distinct Vitamin E effects at different stages of prostate cancer evolution
Njoroge, R. N., Unno, K., Zhao, J. C., Naseem, A. F., Anker, J. F., McGee, W. A., Nonn, L., & Abdulkadir, S. A. (2017) · Scientific Reports · doi:10.1038/s41598-017-16459-2 · Cited by 28
Independent prognostic genes and mechanism investigation for colon cancer
Li, C., Shen, Z., Zhou, Y., & Yu, W. (2018) · Biological Research · doi:10.1186/s40659-018-0158-7 · Cited by 28
Wong‐Bajracharya, J. W. ‐., Lutz, A., Natera, S., Wang, M., Ng, V., Grigoriev, I. V., Martin, F. M., Roessner, U., Anderson, I. C., & Plett, J. M. (2019) · Frontiers in Ecology and Evolution · doi:10.3389/fevo.2019.00010 · Cited by 28
Differential contribution of transcriptomic regulatory layers in the definition of neuronal identity
Ha, K., Sterne-Weiler, T., Morris, Q., Weatheritt, R. J., & Blencowe, B. J. (2021) · Nature Communications · doi:10.1038/s41467-020-20483-8 · Cited by 29
Lee, Y., Nguyen, T. L., Roh, H., Kim, A., Park, J., Lee, J., Kang, H., Kang, H., Sohn, M.-Y., Park, C., et al. (2023) · Fish & Shellfish Immunology · doi:10.1016/j.fsi.2023.109063 · Cited by 27
Phosphorylation of a nuclear condensate regulates cohesion and mRNA retention
McIntyre, A. B. R., Tschan, A. B., Meyer, K., Walser, S., Rai, A. K., Fujita, K., & Pelkmans, L. (2025) · Nature Communications · doi:10.1038/s41467-024-55469-3 · Cited by 27
Matualatupauw, J. C., Bohl, M., Gregersen, S., Hermansen, K., & Afman, L. A. (2017) · International Journal of Obesity · doi:10.1038/ijo.2017.120 · Cited by 27
Liang, J., Liu, Z., Zou, Z., Tang, Y., Zhou, C., Yang, J., Wei, X., & Lu, Y. (2018) · Scientific Reports · doi:10.1038/s41598-018-25002-w · Cited by 27
Integrative transcriptome analysis deciphers mechanisms of nickel contact dermatitis
Wisgrill, L., Werner, P., Jalonen, E., Berger, A., Lauerma, A., Alenius, H. T., & Fyhrquist, N. (2020) · Allergy · doi:10.1111/all.14519 · Cited by 27
A bidirectional switch in the Shank3 phosphorylation state biases synapses toward up- or downscaling
Wu, C.-H., Tatavarty, V., Beltran, P. M., Guerrero, A., Keshishian, H., Krug, K., MacMullan, M. A., Li, L., Carr, S. A., Cottrell, J. R., et al. (2022) · eLife · doi:10.7554/elife.74277 · Cited by 29
Identification of key genes in bovine muscle development by co-expression analysis
Zhang, J., Sheng, H., Pan, C., Wang, S., Yang, M., Hu, C., Wei, D., Wang, Y., & Ma, Y. (2023) · PeerJ · doi:10.7717/peerj.15093 · Cited by 27
Wauchop, M., Rafatian, N., Zhao, Y., Chen, W., Gagliardi, M., Massé, S., Cox, B., Lai, P. F. H., Liang, T., Landau, S., et al. (2023) · Biomaterials · doi:10.1016/j.biomaterials.2023.122255 · Cited by 27
Metadata
- Authors
- Merico, D., Isserlin, R., Stueker, O., Emili, A., & Bader, G. D.
- Affiliations
- University of Toronto (CA)
- Corresponding author
- Merico, Daniele
- Bader, Gary D.
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2010-11-15
- Volume
- 5
- Issue
- 11
- Pages
- e13984
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC2981572
- OpenAlex
- W2097948046
- Cited by
- 2,235
- References
- 58
- Citations by year
- 2026: 89 · 2025: 145 · 2024: 176 · 2023: 216 · 2022: 238 · 2021: 233 · 2020: 237 · 2019: 164 · 2018: 158 · 2017: 145 · 2016: 127 · 2015: 101 · 2014: 79 · 2013: 69 · 2012: 43
- FWCI
- 16.30
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS ONE (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- Funders
- Heart and Stroke Foundation of Canada
- Genome Canada
- Ontario Genomics
- Ontario Genomics Institute
- Hospital for Sick Children
- National Institutes of Health
- National Human Genome Research Institute (P41 P41HG04118, P41HG04118, P41HG004118)
- 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
- gene set enrichment analysis, network visualization, gene set overlap, network clustering, pathway over-representation, gene expression data interpretation, Cytoscape plugin
- MeSH terms
- Algorithms, Breast Neoplasms, Colonic Neoplasms, Estrogens, Female, Humans, Software, Reproducibility of Results, Gene Expression Regulation, Neoplastic, Cluster Analysis, Computational Biology, Internet, Gene Expression Profiling, Gene Regulatory Networks
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.
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