g:Profiler: a web server for functional enrichment analysis and conversions of gene lists (2019 update)

Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

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

Cytoscape: A software Environment for integrated models of biomolecular interaction networks

Shannon, P., Markiel, A., Ozier, O., Baliga, N. S., Wang, J. T., Ramage, D., Amin, N., Schwikowski, B., & Ideker, T. (2003) · Genome Research · doi:10.1101/gr.1239303 · Cited by 51,888 · see citing works

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 · see citing works

Tissue-based map of the human proteome

Uhlén, M., Fagerberg, L., Hallström, B. M., Lindskog, C., Oksvold, P., Mardinoglu, A., Sivertsson, Å., Kampf, C., Sjöstedt, E., Asplund, A., et al. (2015) · Science · doi:10.1126/science.1260419 · Cited by 15,286 · see citing works

Enrichr: a comprehensive gene set enrichment analysis web server 2016 update

Kuleshov, M. V., Jones, M. R., Rouillard, A. D., Fernandez, N. F., Duan, Q., Wang, Z., Koplev, S., Jenkins, S. L., Jagodnik, K. M., Lachmann, A., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw377 · Cited by 10,799 · see citing works

UniProt: a worldwide hub of protein knowledge

The UniProt Consortium (2019) · Nucleic Acids Research · doi:10.1093/nar/gky1049 · Cited by 7,698 · see citing works

Molecular 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

REVIGO summarizes and visualizes long lists of gene ontology terms

Supek, F., Bošnjak, M., Škunca, N., & Šmuc, T. (2011) · PLoS ONE · doi:10.1371/journal.pone.0021800 · Cited by 6,264 · see citing works

KOBAS 2.0: a web server for annotation and identification of enriched pathways and diseases

Xie, C., Mao, X., Huang, J., Ding, Y., Wu, J., Dong, S., Kong, L., Gao, G., Li, C., & Wei, L. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr483 · Cited by 5,078 · see citing works

ClustVis: a web tool for visualizing clustering of multivariate data using Principal Component Analysis and heatmap

Metsalu, T., & Vilo, J. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv468 · Cited by 3,729 · see citing works

The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2018 update

Afgan, E., Baker, D., Batut, B., van den Beek, M., Bouvier, D., Čech, M., Chilton, J., Clements, D., Coraor, N., Grüning, B. A., et al. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky379 · Cited by 3,662 · see citing works

The Reactome Pathway Knowledgebase

Fabregat, A., Jupe, S., Matthews, L. R., Sidiropoulos, K., Gillespie, M. E., Garapati, P. V., Haw, R., Jassal, B., Korninger, F., May, B., et al. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx1132 · Cited by 2,798 · see citing works

DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants

Piñero, J., Bravo, À., Queralt-Rosinach, N., Gutiérrez-Sacristán, A., Deu-Pons, J., Centeno, E., García-García, J., Sanz, F., & Furlong, L. I. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkw943 · Cited by 2,680 · see citing works

agriGO v2.0: a GO analysis toolkit for the agricultural community, 2017 update

Tian, T., Liu, Y., Yan, H., You, Q., Yi, X., Du, Z., Xu, W., & Su, Z. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx382 · Cited by 2,280 · see citing works

TRANSFAC(R) and its module TRANSCompel(R): transcriptional gene regulation in eukaryotes

Matys, V. (2005) · Nucleic Acids Research · doi:10.1093/nar/gkj143 · Cited by 2,179 · see citing works

Pathway enrichment analysis and visualization of omics data using g:Profiler, GSEA, Cytoscape and EnrichmentMap

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

New approach for understanding genome variations in KEGG

Kanehisa, M. I., Sato, Y., Furumichi, M., Morishima, K., & Tanabe, M. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky962 · Cited by 1,845 · see citing works

miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions

Chou, C., Shrestha, S., Yang, C.-D., Chang, N.-W., Lin, Y., Liao, K., Huang, W.-C., Sun, T.-H., Tu, S.-J., Lee, W.-H., et al. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx1067 · Cited by 1,813 · see citing works

Pharmacogenomics Knowledge for Personalized Medicine

Whirl‐Carrillo, M., McDonagh, E. M., Hebert, J. M., Gong, L., Sangkuhl, K., Thorn, C. F., Altman, R. B., & Klein, T. E. (2012) · Clinical Pharmacology & Therapeutics · doi:10.1038/clpt.2012.96 · Cited by 1,791 · see citing works

Ten Years of Pathway Analysis: Current Approaches and Outstanding Challenges

Khatri, P., Sirota, M., & Butte, A. J. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002375 · Cited by 1,569 · see citing works

g:Profiler—a web-based toolset for functional profiling of gene lists from large-scale experiments

Reimand, J., Kull, M., Peterson, H., Hansen, J., & Vilo, J. (2007) · Nucleic Acids Research · doi:10.1093/nar/gkm226 · Cited by 1,525 · see citing works

Ensembl BioMarts: a hub for data retrieval across taxonomic space

Kinsella, R., Kähäri, A., Haider, S., Zamora, J., Proctor, G., Spudich, G., Almeida-King, J., Staines, D., Derwent, P., Kerhornou, A., et al. (2011) · Database J. Biol. Databases Curation · doi:10.1093/database/bar030 · Cited by 1,465 · see citing works

CORUM: the comprehensive resource of mammalian protein complexes—2009

Ruepp, A., Wägele, B., Lechner, M., Brauner, B., Dunger-Kaltenbach, I., Fobo, G., Frishman, G., Montrone, C., & Mewes, H. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp914 · Cited by 1,320 · see citing works

g:Profiler—a web server for functional interpretation of gene lists (2016 update)

Reimand, J., Arak, T., Adler, P., Kolberg, L., Reisberg, S., Peterson, H., & Vilo, J. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw199 · Cited by 1,229 · see citing works

The Reactome pathway Knowledgebase

Fabregat, A., Sidiropoulos, K., Garapati, P., Gillespie, M., Hausmann, K., Haw, R., Jassal, B., Jupe, S., Korninger, F., McKay, S., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkv1351 · Cited by 1,201 · see citing works

WebGestalt 2017: a more comprehensive, powerful, flexible and interactive gene set enrichment analysis toolkit

Wang, J., Vasaikar, S. V., Shi, Z., Greer, M., & Zhang, B. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx356 · Cited by 1,161 · see citing works

WikiPathways: a multifaceted pathway database bridging metabolomics to other omics research

Slenter, D., Kutmon, M., Hanspers, K., Riutta, A., Windsor, J., Nunes, N. M., Mélius, J., Cirillo, E., Coort, S. L., Digles, D., et al. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx1064 · Cited by 910 · see citing works

Meta- and Orthogonal Integration of Influenza “OMICs” Data Defines a Role for UBR4 in Virus Budding

Tripathi, S., Pohl, M. O., Zhou, Y., Rodríguez-Frandsen, A., Wang, G., Stein, D. A., Moulton, H. M., DeJesus, P., Che, J., Mulder, L. C. F., et al. (2015) · Cell Host & Microbe · doi:10.1016/j.chom.2015.11.002 · Cited by 846 · see citing works

WormBase ParaSite − a comprehensive resource for helminth genomics

Howe, K., Bolt, B. J., Shafie, M., Kersey, P. J., & Berriman, M. (2016) · Molecular and Biochemical Parasitology · doi:10.1016/j.molbiopara.2016.11.005 · Cited by 751 · see citing works

Expansion of the Human Phenotype Ontology (HPO) knowledge base and resources

Köhler, S., Carmody, L., Vasilevsky, N., Jacobsen, J. O. B., Danis, D., Gourdine, J.-P., Gargano, M., Harris, N. L., Matentzoglu, N., McMurry, J. A., et al. (2019) · Nucleic Acids Research · doi:10.1093/nar/gky1105 · Cited by 677 · see citing works

CORUM: the comprehensive resource of mammalian protein complexes—2019

Giurgiu, M., Reinhard, J., Brauner, B., Dunger-Kaltenbach, I., Fobo, G., Frishman, G., Montrone, C., & Ruepp, A. (2019) · Nucleic Acids Research · doi:10.1093/nar/gky973 · Cited by 595 · see citing works

g:Profiler—a web server for functional interpretation of gene lists (2011 update)

Reimand, J., Arak, T., & Vilo, J. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr378 · Cited by 504 · see citing works

Ensembl variation resources

Hunt, S. E., McLaren, W. M., Gil, L., Thormann, A., Schuilenburg, H., Sheppard, D., Parton, A., Armean, I. M., Trevanion, S. J., Flicek, P., et al. (2018) · Database · doi:10.1093/database/bay119 · Cited by 455 · see citing works

Mining for coexpression across hundreds of datasets using novel rank aggregation and visualization methods

Adler, P., Kolde, R., Kull, M., Tkachenko, A., Peterson, H., Reimand, J., & Vilo, J. (2009) · Genome biology · doi:10.1186/gb-2009-10-12-r139 · Cited by 151 · see citing works

Impact of outdated gene annotations on pathway enrichment analysis

Wadi, L., Meyer, M., Weiser, J., Stein, L. D., & Reimand, J. (2016) · Nature Methods · doi:10.1038/nmeth.3963 · Cited by 138 · see citing works

Consistently faster and smaller compressed bitmaps with Roaring

Daniel Lemire, A., Ssi-Yan-Kai, G., & Owen Kaser, B. (2016) · Software Practice and Experience · doi:10.1002/spe.2402 · Cited by 57 · see citing works

Improving the Sequence Ontology terminology for genomic variant annotation

Cunningham, F., Moore, B., Ruiz-Schultz, N., Ritchie, G., & Eilbeck, K. (2015) · Journal of Biomedical Semantics · doi:10.1186/s13326-015-0030-4 · Cited by 26 · see citing works

Gene expression analysis of human adipose tissue-derived stem cells during the initial steps of in vitro osteogenesis

Robert, A. W., Angulski, A. B. B., Spangenberg, L., et al. (2018) · Scientific Reports · doi:10.1038/s41598-018-22991-6 · Cited by 22 · see citing works

funcExplorer: a tool for fast data-driven functional characterisation of high-throughput expression data

Kolberg, L., Kuzmin, I., Adler, P., et al. (2018) · BMC Genomics · doi:10.1186/s12864-018-5176-x · Cited by 5 · see citing works

Organoids

Zhao, Z., Chen, X., Dowbaj, A. M., Sljukic, A., Bratlie, K., Lin, L., Fong, E. L. S., Balachander, G. M., Chen, Z., Soragni, A., et al. (2022) · Nature Reviews Methods Primers · doi:10.1038/s43586-022-00174-y · Cited by 1,001 · see citing works

Organ aging signatures in the plasma proteome track health and disease

Oh, H. S.-H., Rutledge, J., Nachun, D., Pálovics, R., Abiose, O., Moran-Losada, P., Channappa, D., Urey, D. Y., Kim, K., Sung, Y. J., et al. (2023) · Nature · doi:10.1038/s41586-023-06802-1 · Cited by 634 · see citing works

Genome-wide meta-analysis, fine-mapping and integrative prioritization implicate new Alzheimer’s disease risk genes

Schwartzentruber, J., Cooper, S., Liu, J. Z., Barrio-Hernandez, I., Bello, E., Kumasaka, N., Young, A. M. H., Franklin, R. J. M., Johnson, T., Estrada, K., et al. (2021) · Nature Genetics · doi:10.1038/s41588-020-00776-w · Cited by 532 · see citing works

Spatial deconvolution of HER2-positive breast cancer delineates tumor-associated cell type interactions

Andersson, A., Larsson, L., Stenbeck, L., Salmén, F., Ehinger, A., Wu, S. Z., Al-Eryani, G., Roden, D., Swarbrick, A., Borg, Å., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-26271-2 · Cited by 404 · see citing works

Senescence atlas reveals an aged-like inflamed niche that blunts muscle regeneration

Moiseeva, V., Cisneros, A., Sica, V., Deryagin, O., Lai, Y., Jung, S., Andrés, E., An, J., Segalés, J., Ortet, L., et al. (2023) · Nature · doi:10.1038/s41586-022-05535-x · Cited by 423 · see citing works

Promotion of cholangiocarcinoma growth by diverse cancer-associated fibroblast subpopulations

Affo, S., Nair, A., Brundu, F., Ravichandra, A., Bhattacharjee, S., Matsuda, M., Chin, L., Filliol, A., Wen, W., Song, X., et al. (2021) · Cancer Cell · doi:10.1016/j.ccell.2021.03.012 · Cited by 416 · see citing works

Integrative Single-Cell RNA-Seq and ATAC-Seq Analysis of Human Developmental Hematopoiesis

Ranzoni, A. M., Tangherloni, A., Berest, I., Riva, S. G., Myers, B., Strzelecka, P. M., Xu, J., Panada, E., Mohorianu, I., Zaugg, J. B., et al. (2021) · Cell Stem Cell · doi:10.1016/j.stem.2020.11.015 · Cited by 331 · see citing works

Molecular signatures underlying neurofibrillary tangle susceptibility in Alzheimer’s disease

Otero-Garcia, M., Mahajani, S. U., Wakhloo, D., Tang, W., Xue, Y.-Q., Morabito, S., Pan, J., Oberhauser, J., Madira, A. E., Shakouri, T., et al. (2022) · Neuron · doi:10.1016/j.neuron.2022.06.021 · Cited by 262 · see citing works

Pathogenic variants damage cell composition and single cell transcription in cardiomyopathies

Reichart, D., Lindberg, E. L., Maatz, H., Miranda, A. M. A., Viveiros, A., Shvetsov, N., Gärtner, A., Nadelmann, E. R., Lee, M., Kanemaru, K., et al. (2022) · Science · doi:10.1126/science.abo1984 · Cited by 240 · see citing works

In vivo CRISPR screens reveal the landscape of immune evasion pathways across cancer

Dubrot, J., Du, P. P., Lane-Reticker, S. K., Kessler, E. A., Muscato, A. J., Mehta, A., Freeman, S. S., Allen, P. M., Olander, K. E., Ockerman, K. M., et al. (2022) · Nature Immunology · doi:10.1038/s41590-022-01315-x · Cited by 218 · see citing works

Xist ribonucleoproteins promote female sex-biased autoimmunity

Dou, D. R., Zhao, Y., Belk, J. A., Zhao, Y., Casey, K. M., Chen, D. C., Li, R., Yu, B., Srinivasan, S., Abe, B. T., et al. (2024) · Cell · doi:10.1016/j.cell.2023.12.037 · Cited by 233 · see citing works

Large-scale plasma proteomic analysis identifies proteins and pathways associated with dementia risk

Walker, K. A., Chen, J., Zhang, J., Fornage, M., Yang, Y., Zhou, L., Grams, M. E., Tin, A., Daya, N., Hoogeveen, R. C., et al. (2021) · Nature Aging · doi:10.1038/s43587-021-00064-0 · Cited by 212 · see citing works

Trained Immunity-Promoting Nanobiologic Therapy Suppresses Tumor Growth and Potentiates Checkpoint Inhibition

Priem, B., van Leent, M. M. T., Teunissen, A. J. P., Sofias, A. M., Mourits, V. P., Willemsen, L., Klein, E. D., Oosterwijk, R. S., Meerwaldt, A. E., Munitz, J., et al. (2020) · Cell · doi:10.1016/j.cell.2020.09.059 · Cited by 222 · see citing works

<i>Trem2</i> promotes anti-inflammatory responses in microglia and is suppressed under pro-inflammatory conditions

Liu, W., Taso, O., Wang, R., Bayram, S., Graham, A. C., Garcia-Reitboeck, P., Mallach, A., Andrews, W. D., Piers, T. M., Botia, J. A., et al. (2020) · Human Molecular Genetics · doi:10.1093/hmg/ddaa209 · Cited by 214 · see citing works

Mitochondrial dynamics maintain muscle stem cell regenerative competence throughout adult life by regulating metabolism and mitophagy

Hong, X., Isern, J., Campanario, S., Perdiguero, E., Ramírez-Pardo, I., Segalés, J., Hernansanz-Agustín, P., Curtabbi, A., Deryagin, O., Pollán, A., et al. (2022) · Cell stem cell · doi:10.1016/j.stem.2022.07.009 · Cited by 213 · see citing works

A genome-wide atlas of co-essential modules assigns function to uncharacterized genes

Wainberg, M., Kamber, R. A., Balsubramani, A., Meyers, R. M., Sinnott-Armstrong, N., Hornburg, D., Jiang, L., Chan, J., Jian, R., Gu, M., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00840-z · Cited by 204 · see citing works

Super-resolved spatial transcriptomics by deep data fusion

Bergenstråhle, L., He, B., Bergenstråhle, J., Abalo, X., Mirzazadeh, R., Thrane, K., Ji, A. L., Andersson, A., Larsson, L., Stakenborg, N., et al. (2022) · Nature Biotechnology · doi:10.1038/s41587-021-01075-3 · Cited by 188 · see citing works

A genetic map of the mouse dorsal vagal complex and its role in obesity

Ludwig, M. Q., Cheng, W., Gordian, D., Lee, J., Paulsen, S. J., Hansen, S. N., Egerod, K. L., Barkholt, P., Rhodes, C. J., Secher, A., et al. (2021) · Nature Metabolism · doi:10.1038/s42255-021-00363-1 · Cited by 186 · see citing works

Gut Microbiota Dysbiosis Is Associated with Elevated Bile Acids in Parkinson’s Disease

Li, P., Killinger, B. A., Ensink, E., Beddows, I., Yilmaz, A., Lubben, N., Lamp, J., Schilthuis, M., Vega, I. E., Woltjer, R., et al. (2021) · Metabolites · doi:10.3390/metabo11010029 · Cited by 146 · see citing works

Acquisition of epithelial plasticity in human chronic liver disease

Gribben, C., Galanakis, V., Calderwood, A., Williams, E. C., Chazarra-Gil, R., Larraz, M., Frau, C., Puengel, T., Guillot, A., Rouhani, F. J., et al. (2024) · Nature · doi:10.1038/s41586-024-07465-2 · Cited by 142 · see citing works

Joint single-cell measurements of nuclear proteins and RNA in vivo

Chung, H., Parkhurst, C. N., Magee, E. M., Phillips, D., Habibi, E., Chen, F., Yeung, B. Z., Waldman, J., Artis, D., & Regev, A. (2021) · Nature Methods · doi:10.1038/s41592-021-01278-1 · Cited by 144 · see citing works

Small extracellular vesicles from young adipose-derived stem cells prevent frailty, improve health span, and decrease epigenetic age in old mice

Sanz-Ros, J., Romero-García, N., Mas-Bargues, C., Monleón, D., Gordevicius, J., Brooke, R. T., Dromant, M., Díaz, A., Derevyanko, A., Guío-Carrión, A., et al. (2022) · Science Advances · doi:10.1126/sciadv.abq2226 · Cited by 131 · see citing works

Manumycin polyketides act as molecular glues between UBR7 and P53

Isobe, Y., Okumura, M., McGregor, L. M., Brittain, S. M., Jones, M. D., Liang, X., White, R., Forrester, W., McKenna, J. M., Tallarico, J. A., et al. (2020) · Nature Chemical Biology · doi:10.1038/s41589-020-0557-2 · Cited by 124 · see citing works

Incorporation of a nucleoside analog maps genome repair sites in postmitotic human neurons

Reid, D. A., Reed, P. J., Schlachetzki, J. C. M., Nitulescu, I. I., Chou, G., Tsui, E. C., Jones, J. R., Chandran, S., Lu, A. T., McClain, C. A., et al. (2021) · Science · doi:10.1126/science.abb9032 · Cited by 121 · see citing works

Accumulation of cytotoxic T cells in the aged CNS leads to axon degeneration and contributes to cognitive and motor decline

Groh, J., Knöpper, K., Arampatzi, P., Yuan, X., Lößlein, L., Saliba, A.-E., Kastenmüller, W., & Martini, R. (2021) · Nature Aging · doi:10.1038/s43587-021-00049-z · Cited by 118 · see citing works

Neuronal and glial 3D chromatin architecture informs the cellular etiology of brain disorders

Hu, B., Won, H., Mah, W., Park, R. B., Kassim, B., Spiess, K., Kozlenkov, A., Crowley, C. A., Pochareddy, S., The PsychENCODE Consortium, et al. (2021) · Nature Communications · doi:10.1038/s41467-021-24243-0 · Cited by 103 · see citing works

IFN signaling and neutrophil degranulation transcriptional signatures are induced during SARS-CoV-2 infection

Rosa, B. A., Ahmed, M., Singh, D. K., Choreño-Parra, J. A., Cole, J., Jiménez-Álvarez, L. A., Rodríguez-Reyna, T. S., Singh, B., Gonzalez, O., Carrion, R., et al. (2021) · Communications Biology · doi:10.1038/s42003-021-01829-4 · Cited by 106 · see citing works

Paralog buffering contributes to the variable essentiality of genes in cancer cell lines

De Kegel, B., & Ryan, C. J. (2019) · PLOS Genetics · doi:10.1371/journal.pgen.1008466 · Cited by 92 · see citing works

Vitamin d status modulates mitochondrial oxidative capacities in skeletal muscle: role in sarcopenia

Salles, J., Chanet, A., Guillet, C., Vaes, A. M., Brouwer-Brolsma, E. M., Rocher, C., Giraudet, C., Patrac, V., Meugnier, E., Montaurier, C., et al. (2022) · Communications Biology · doi:10.1038/s42003-022-04246-3 · Cited by 73 · see citing works

The epithelial-specific ER stress sensor ERN2/IRE1β enables host-microbiota crosstalk to affect colon goblet cell development

Grey, M. J., De Luca, H., Ward, D. V., Kreulen, I. A. M., Bugda Gwilt, K., Foley, S. E., Thiagarajah, J. R., McCormick, B. A., Turner, J. R., & Lencer, W. I. (2022) · Journal of Clinical Investigation · doi:10.1172/jci153519 · Cited by 65 · see citing works

Multi cell line analysis of lysosomal proteomes reveals unique features and novel lysosomal proteins

Akter, F., Ponnaiyan, S., Kögler-Mohrbacher, B., Bleibaum, F., Damme, M., Renard, B. Y., & Winter, D. (2020) · doi:10.1101/2020.12.21.423747 · Cited by 55 · see citing works

Oncology and Pharmacogenomics Insights in Polycystic Ovary Syndrome: An Integrative Analysis

Yumiceba, V., López-Cortés, A., Pérez-Villa, A., Yumiseba, I., Guerrero, S., García-Cárdenas, J. M., Armendáriz-Castillo, I., Guevara-Ramírez, P., Leone, P. E., Zambrano, A. K., et al. (2020) · Frontiers in Endocrinology · doi:10.3389/fendo.2020.585130 · Cited by 40 · see citing works

Sparse dictionary learning recovers pleiotropy from human cell fitness screens

Pan, J., Kwon, J. J., Talamas, J. A., Borah, A. A., Vazquez, F., Boehm, J. S., Tsherniak, A., Zitnik, M., McFarland, J. M., & Hahn, W. C. (2022) · Cell Systems · doi:10.1016/j.cels.2021.12.005 · Cited by 37 · see citing works

CTNND2 moderates the pace of synaptic maturation and links human evolution to synaptic neoteny

Assendorp, N., Fossati, M., Libé-Philippot, B., Christopoulou, E., Depp, M., Rapone, R., Dingli, F., Loew, D., Vanderhaeghen, P., & Charrier, C. (2024) · Cell Reports · doi:10.1016/j.celrep.2024.114797 · Cited by 32 · see citing works

Heritability of interpack aggression in a wild pedigreed population of North American grey wolves

vonHoldt, B. M., DeCandia, A. L., Heppenheimer, E., Janowitz‐Koch, I., Shi, R., Zhou, H., German, C. A., Brzeski, K. E., Cassidy, K. A., Stahler, D. R., et al. (2020) · Molecular Ecology · doi:10.1111/mec.15349 · Cited by 22 · see citing works

Actionable cancer vulnerability due to translational arrest, p53 aggregation and ribosome biogenesis stress evoked by the disulfiram metabolite CuET

Kanellis, D. C., Zisi, A., Skrott, Z., Lemmens, B., Espinoza, J. A., Kosar, M., Björkman, A., Li, X., Arampatzis, S., Bartkova, J., et al. (2023) · Cell Death &amp; Differentiation · doi:10.1038/s41418-023-01167-4 · Cited by 27 · see citing works

Single-cell RNA sequencing reveals maturation trajectory in human pluripotent stem cell-derived cardiomyocytes in engineered tissues

Cheng, S., Brenière-Letuffe, D., Ahola, V., Wong, A. O. T., Keung, H. Y., Gurung, B., Zheng, Z., Costa, K. D., Lieu, D. K., Keung, W., et al. (2023) · iScience · doi:10.1016/j.isci.2023.106302 · Cited by 23 · see citing works

Variant-specific vaccination induces systems immune responses and potent in vivo protection against SARS-CoV-2

Peng, L., Renauer, P. A., Ökten, A., Fang, Z., Park, J. J., Zhou, X., Lin, Q., Dong, M. B., Filler, R., Xiong, Q., et al. (2022) · Cell Reports Medicine · doi:10.1016/j.xcrm.2022.100634 · Cited by 21 · see citing works

COPD patients with chronic bronchitis and higher sputum eosinophil counts show increased type‐2 and PDE4 gene expression in sputum

Singh, D., Bassi, M., Balzano, D., Lucci, G., Emirova, A., Anna Nandeuil, M., Jellema, G., Afolabi, E. K., Leaker, B., Kornmann, O., et al. (2021) · Journal of Cellular and Molecular Medicine · doi:10.1111/jcmm.16146 · Cited by 20 · see citing works

In-depth profiling and quantification of the lysine acetylome in hepatocellular carcinoma with a trapped ion mobility mass spectrometer

Xu, J., Guan, X., Jia, X., Li, H., Chen, R., & Lu, Y. (2022) · Molecular &amp; Cellular Proteomics · doi:10.1016/j.mcpro.2022.100255 · Cited by 19 · see citing works

Genomic Insights into the Population History and Adaptive Traits of Latin American Criollo Cattle

Ward, J. A., Ng'ang'a, S. I., Randhawa, I. A. S., McHugo, G. P., O'Grady, J. F., Flórez, J. M., Browne, J. A., Pérez O’Brien, A. M., Landaeta-Hernández, A. J., Garcia, J. F., et al. (2024) · Royal Society Open Science · doi:10.1098/rsos.231388 · Cited by 17 · see citing works

Broad functional profiling of fission yeast proteins using phenomics and machine learning

Rodríguez-López, M., Bordin, N., Lees, J., Scholes, H., Hassan, S., Saintain, Q., Kamrad, S., Orengo, C., & Bähler, J. (2023) · eLife · doi:10.7554/elife.88229.3 · Cited by 18 · see citing works

Dietary fish oil enriched in very-long-chain polyunsaturated fatty acid reduces cardiometabolic risk factors and improves retinal function

Yang, Z.-H., Gorusupudi, A., Lydic, T. A., Mondal, A. K., Sato, S., Yamazaki, I., Yamaguchi, H., Tang, J., Rojulpote, K. V., Lin, A. B., et al. (2023) · iScience · doi:10.1016/j.isci.2023.108411 · Cited by 9 · see citing works

Atypical cellular responses mediated by intracellular constitutive active TrkB (NTRK2) kinase domains and a solely intracellular NTRK2-fusion oncogene

Gupta, R., Dittmeier, M., Wohlleben, G., Nickl, V., Bischler, T., Luzak, V., Wegat, V., Doll, D., Sodmann, A., Bady, E., et al. (2024) · Cancer Gene Therapy · doi:10.1038/s41417-024-00809-0 · Cited by 7 · see citing works

Single-cell resolution analysis of the crosstalk between chemogenically activated astrocytes and microglia

Philtjens, S., Turnbull, M. T., Thedy, B. P., Moon, Y., & Kim, J. (2020) · doi:10.1101/2020.04.27.064881 · Cited by 7 · see citing works

Human Adult Astrocyte Extracellular Vesicle Transcriptomics Study Identifies Specific RNAs Which Are Preferentially Secreted as EV Luminal Cargo

Shanthi, K., Fischer, D., Sharma, A., Kiviniemi, A., Kaakinen, M., Vainio, S., & Bart, G. (2023) · Genes · doi:10.3390/genes14040853 · Cited by 5 · see citing works

Deep Trans-Omic Network Fusion for Molecular Mechanism of Alzheimer’s Disease

Xie, L., Raj, Y., Varathan, P., He, B., Yu, M., Nho, K., Salama, P., Saykin, A. J., & Yan, J. (2024) · Journal of Alzheimer's Disease · doi:10.3233/jad-240098 · Cited by 2 · see citing works

GOLDEN fusion: a graph-oriented learning with domain-embedding network fusion for generating super gene sets in functional genomics

Li, Q., Nichols, C., Welner, R. S., Chen, J. Y., Ku, W.-S., & Yue, Z. (2026) · Briefings in Bioinformatics · doi:10.1093/bib/bbag244

TFXcan reveals transcription factor programs driving GWAS loci

Adeluwa, T., Salazar-Magaña, S., Sumner, S., Gona, S., Nyasimi, F., Carbonetto, P., Baca, S. C., Freedman, M., Gusev, A., Liu, B., et al. (2026) · Cell Genomics · doi:10.1016/j.xgen.2026.101398

Ensembl BioMarts: a hub for data retrieval across taxonomic space

Kinsella, R., Kähäri, A., Haider, S., Zamora, J., Proctor, G., Spudich, G., Almeida-King, J., Staines, D., Derwent, P., Kerhornou, A., et al. (2011) · Database J. Biol. Databases Curation · doi:10.1093/database/bar030 · Cited by 1,465 · see citing works

Ensembl 2023

Martin, F. J., Amode, M. R., Aneja, A., Austine-Orimoloye, O., Azov, A. G., Barnes, I., Becker, A., Bennett, R., Berry, A. E., Bhai, J. N. N. T., et al. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac958 · Cited by 980 · see citing works

Deriving the consequences of genomic variants with the Ensembl API and SNP Effect Predictor

McLaren, W. M., Yates, B., Ríos, D., Chen, Y., Flicek, P., & Cunningham, F. M. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq330 · Cited by 1,586 · see citing works

Ensembl 2009

Hubbard, T., Aken, B. L., Ayling, S., Ballester, B., Beal, K. M., Bragin, E., Brent, S., Chen, Y., Clapham, P., Clarke, L., et al. (2008) · Nucleic Acids Research · doi:10.1093/nar/gkn828 · Cited by 671 · see citing works

Ensembl 2005

Hubbard, T. (2004) · Nucleic Acids Research · doi:10.1093/nar/gki138 · Cited by 348 · see citing works