The human protein atlas: a spatial map of the human proteome
Open accessAbstract
The correct spatial distribution of proteins is vital for their function and often mis-localization or ectopic expression leads to diseases. For more than a decade, the Human Protein Atlas (HPA) has constituted a valuable tool for researchers studying protein localization and expression in human tissues and cells. The centerpiece of the HPA is its unique antibody collection for mapping the entire human proteome by immunohistochemistry and immunocytochemistry. By these approaches, more than 10 million images showing protein expression patterns at a single-cell level were generated and are publicly available at www.proteinatlas.org. The antibody-based approach is combined with transcriptomics data for an overview of global expression profiles. The present article comprehensively describes the HPA database functions and how users can utilize it for their own research as well as discusses the future path of spatial proteomics.
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Target expression data was primarily extracted from GTEx, the Human Protein Atlas, UniProt and TISSUES.
“Target expression data was primarily extracted from GTEx (12), the Human Protein Atlas (HPA) (13), UniProt and TISSUES (14).”
From TCRD and pharos 2021: mining the human proteome for disease biology (2021) · cites this paper as [13]
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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
The cancer genome atlas pan-cancer analysis project
The Cancer Genome Atlas Research Network, Weinstein, J. N., Collisson, E. A., Mills, G. B., Shaw, K. R. M., Ozenberger, B. A., Ellrott, K., Shmulevich, I., Sander, C., & Stuart, J. M. (2013) · Nature Genetics · doi:10.1038/ng.2764 · Cited by 9,092 · see citing works
The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans
The GTEx Consortium, Ardlie, K. G., Deluca, D. S., Segrè, A. V., Sullivan, T. J., Young, T. R., Gelfand, E. T., Trowbridge, C. A., Maller, J. B., Tukiainen, T., et al. (2015) · Science · doi:10.1126/science.1262110 · Cited by 5,062 · see citing works
Fagerberg, L., Hallström, B. M., Oksvold, P., Kampf, C., Djureinovic, D., Odeberg, J., Habuka, M., Tahmasebpoor, S., Danielsson, A., Edlund, K., et al. (2014) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m113.035600 · Cited by 3,665 · see citing works
A pathology atlas of the human cancer transcriptome
Uhlen, M., Zhang, C., Lee, S., Sjöstedt, E., Fagerberg, L., Bidkhori, G., Benfeitas, R., Arif, M., Liu, Z., Edfors, F., et al. (2017) · Science · doi:10.1126/science.aan2507 · Cited by 3,371 · see citing works
A subcellular map of the human proteome
Thul, P. J., Åkesson, L., Wiking, M., Mahdessian, D., Geladaki, A., Ait Blal, H., Alm, T., Asplund, A., Björk, L., Breckels, L. M., et al. (2017) · Science · doi:10.1126/science.aal3321 · Cited by 2,813 · see citing works
Towards a knowledge-based Human Protein Atlas
Uhlen, M., Oksvold, P., Fagerberg, L., Lundberg, E., Jonasson, K., Forsberg, M., Zwahlen, M., Kampf, C., Wester, K., Hober, S., et al. (2010) · Nature Biotechnology · doi:10.1038/nbt1210-1248 · Cited by 2,440 · see citing works
A draft map of the human proteome
Kim, M.-S., Pinto, S. M., Getnet, D., Nirujogi, R. S., Manda, S. S., Chaerkady, R., Madugundu, A. K., Kelkar, D. S., Isserlin, R., Jain, S., et al. (2014) · Nature · doi:10.1038/nature13302 · Cited by 2,198 · see citing works
Visualizing Spatiotemporal Dynamics of Multicellular Cell-Cycle Progression
Sakaue-Sawano, A., Kurokawa, H., Morimura, T., Hanyu, A., Hama, H., Osawa, H., Kashiwagi, S., Fukami, K., Miyata, T., Miyoshi, H., et al. (2008) · Cell · doi:10.1016/j.cell.2007.12.033 · Cited by 2,123 · see citing works
Mass-spectrometry-based draft of the human proteome
Wilhelm, M., Schlegl, J., Hahne, H., Gholami, A. M., Lieberenz, M., Savitski, M. M., Ziegler, E., Butzmann, L., Gessulat, S., Marx, H., et al. (2014) · Nature · doi:10.1038/nature13319 · Cited by 1,820 · see citing works
A Human Protein Atlas for Normal and Cancer Tissues Based on Antibody Proteomics
Uhlén, M., Björling, E., Agaton, C., Szigyarto, C. A., Amini, B., Andersen, E., Andersson, A., Angelidou, P., Asplund, A., Asplund, C., et al. (2005) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m500279-mcp200 · Cited by 1,543 · see citing works
Yates, A. D., Akanni, W. A., Amode, M. R., Barrell, D. G., Billis, K., Carvalho‐Silva, D., Cummins, C. A., Clapham, P., Fitzgerald, S. F., Gil, L., et al. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv1157 · Cited by 1,246 · see citing works
A proposal for validation of antibodies
Uhlen, M., Bandrowski, A., Carr, S., Edwards, A., Ellenberg, J., Lundberg, E., Rimm, D. L., Rodriguez, H., Hiltke, T., Snyder, M., et al. (2016) · Nature Methods · doi:10.1038/nmeth.3995 · Cited by 626 · see citing works
Nilsson, P., Paavilainen, L., Larsson, K., Ödling, J., Sundberg, M., Andersson, A., Kampf, C., Persson, A., Szigyarto, C., Ottosson, J., et al. (2005) · Proteomics · doi:10.1002/pmic.200500072 · Cited by 269 · see citing works
Stadler, C., Rexhepaj, E., Singan, V. R., Murphy, R. F., Pepperkok, R., Uhlén, M., Simpson, J. C., & Lundberg, E. K. (2013) · Nature Methods · doi:10.1038/nmeth.2377 · Cited by 265 · see citing works
The human testis-specific proteome defined by transcriptomics and antibody-based profiling
Djureinovic, D., Fagerberg, L., Hallström, B. M., Danielsson, A., Lindskog, C., Uhlén, M., & Pontén, F. (2014) · Molecular Human Reproduction · doi:10.1093/molehr/gau018 · Cited by 219 · see citing works
Toward a Confocal Subcellular Atlas of the Human Proteome
Barbe, L., Lundberg, E. K., Oksvold, P., Stenius, A., Lewin, E., Björling, E., Asplund, A., Pontén, F., Brismar, H., Uhlén, M., et al. (2007) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m700325-mcp200 · Cited by 158 · see citing works
Yu, N., Hallström, B. M., Fagerberg, L., Pontén, F., Kawaji, H., Carninci, P., Forrest, A. R. R., Hayashizaki, Y., Uhlén, M., & Daub, C. O. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv608 · Cited by 115 · see citing works
A single fixation protocol for proteome-wide immunofluorescence localization studies
Stadler, C., Skogs, M., Brismar, H., Uhlén, M., & Lundberg, E. K. (2009) · Journal of Proteomics · doi:10.1016/j.jprot.2009.10.012 · Cited by 103 · see citing works
The human liver‐specific proteome defined by transcriptomics and antibody‐based profiling
Kampf, C., Mardinoğlu, A., Fagerberg, L., Hallström, B. M., Edlund, K., Lundberg, E. K., Pontén, F., Nielsen, J., & Uhlén, M. (2014) · The FASEB Journal · doi:10.1096/fj.14-250555 · Cited by 81 · see citing works
Omenn, G. S., Lane, L., Lundberg, E. K., Beavis, R. C., Overall, C. M., & Deutsch, E. W. (2016) · Journal of Proteome Research · doi:10.1021/acs.jproteome.6b00511 · Cited by 77 · see citing works
The potential clinical impact of the tissue-based map of the human proteome
Lindskog, C. (2015) · Expert Review of Proteomics · doi:10.1586/14789450.2015.1040771 · Cited by 67 · see citing works
The lung‐specific proteome defined by integration of transcriptomics and antibody‐based profiling
Lindskog, C., Fagerberg, L., Hallström, B. M., Edlund, K., Hellwig, B., Rahnenführer, J., Kampf, C., Uhlén, M., Pontén, F., & Micke, P. (2014) · The FASEB Journal · doi:10.1096/fj.14-254862 · Cited by 60 · see citing works
Stadler, C., Hjelmare, M., Neumann, B., Jonasson, K., Pepperkok, R., Uhlén, M., & Lundberg, E. K. (2012) · Journal of Proteomics · doi:10.1016/j.jprot.2012.01.030 · Cited by 37 · see citing works
Antibody Validation in Bioimaging Applications Based on Endogenous Expression of Tagged Proteins
Skogs, M., Stadler, C., Schutten, R., Hjelmare, M., Gnann, C., Björk, L., Poser, I., Hyman, A. A., Uhlén, M., & Lundberg, E. K. (2016) · Journal of Proteome Research · doi:10.1021/acs.jproteome.6b00821 · Cited by 18 · see citing works
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Baysoy, A., Bai, Z., Satija, R., & Fan, R. (2023) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-023-00615-w · Cited by 1,037 · see citing works
A human cell atlas of fetal gene expression
Cao, J., O’Day, D. R., Pliner, H. A., Kingsley, P. D., Deng, M., Daza, R. M., Zager, M. A., Aldinger, K. A., Blecher-Gonen, R., Zhang, F., et al. (2020) · Science · doi:10.1126/science.aba7721 · Cited by 764 · see citing works
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Yao, H., Lan, J., Li, C., Shi, H., Brosseau, J., Wang, H., Lu, H., Fang, C., Zhang, Y., Liang, L., et al. (2019) · Nature Biomedical Engineering · doi:10.1038/s41551-019-0375-6 · Cited by 572 · see citing works
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Goswami, R., Subramanian, G., Silayeva, L., Newkirk, I., Doctor, D. M., Chawla, K., Chattopadhyay, S., Chandra, D., Chilukuri, N., & Betapudi, V. (2019) · Frontiers in Oncology · doi:10.3389/fonc.2019.00297 · Cited by 351 · see citing works
Hu, L., Chen, M., Chen, X., Zhao, C., Fang, Z., Wang, H., & Dai, H. (2020) · Cell Death and Disease · doi:10.1038/s41419-020-2476-2 · Cited by 327 · see citing works
Deep learning enables high-quality and high-throughput prediction of enzyme commission numbers
Ryu, J. Y., Kim, H. U., & Lee, S. Y. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1821905116 · Cited by 294 · see citing works
Aminoacyl-tRNA synthetases as therapeutic targets
Kwon, N. H., Fox, P. L., & Kim, S. (2019) · Nature Reviews Drug Discovery · doi:10.1038/s41573-019-0026-3 · Cited by 271 · see citing works
The Human Protein Atlas—Spatial localization of the human proteome in health and disease
Digre, A., & Lindskog, C. (2020) · Protein Science · doi:10.1002/pro.3987 · Cited by 247 · see citing works
Spatiotemporal omics for biology and medicine
Liu, L., Chen, A., Li, Y., Mulder, J., Heyn, H., & Xu, X. (2024) · Cell · doi:10.1016/j.cell.2024.07.040 · Cited by 238 · see citing works
Bond, M. J., & Crews, C. M. (2021) · RSC Chemical Biology · doi:10.1039/d1cb00011j · Cited by 227 · see citing works
A high-stringency blueprint of the human proteome
Adhikari, S., Nice, E. C., Deutsch, E. W., Lane, L., Omenn, G. S., Pennington, S. R., Paik, Y.-K., Overall, C. M., Corrales, F. J., Cristea, I. M., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-19045-9 · Cited by 210 · see citing works
The neXtProt knowledgebase in 2020: data, tools and usability improvements
Zahn‐Zabal, M., Michel, P.-A., Gateau, A., Nikitin, F., Schaeffer, M., Audot, E., Gaudet, P., Duek, P. D., Teixeira, D., de Laval, V. R., et al. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz995 · Cited by 215 · see citing works
Abedini, A., Levinsohn, J. L., Klötzer, K. A., Dumoulin, B., Ma, Z., Frederick, J., Dhillon, P., Balzer, M. S., Shrestha, R., Liu, H., et al. (2024) · Nature Genetics · doi:10.1038/s41588-024-01802-x · Cited by 254 · see citing works
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Ma, C., Cong, Y., & Zhang, H. (2020) · The American Journal of Gastroenterology · doi:10.14309/ajg.0000000000000691 · Cited by 195 · see citing works
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Diamant, I., Clarke, D. J. B., Evangelista, J. E., Lingam, N., & Ma’ayan, A. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkae1080 · Cited by 149 · see citing works
Pharos 2023: an integrated resource for the understudied human proteome
Kelleher, K. J., Sheils, T. K., Mathias, S. L., Yang, J. J., Metzger, V. T., Siramshetty, V. B., Nguyen, D.-T., Jensen, L. J., Vidović, D., Schürer, S. C., et al. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkac1033 · Cited by 137 · see citing works
Solari, J. I. G., Filippi‐Chiela, E. C., Pilar, E. F. S., Nunes, V. B. D. S., Gonzalez, E. A., Figueiró, F., Andrade, C., & Klamt, F. (2020) · BMC Cancer · doi:10.1186/s12885-020-06964-5 · Cited by 129 · see citing works
A comparison of gene expression and DNA methylation patterns across tissues and speciesPreprint
Blake, L. E., Roux, J., Hernando-Herraez, I., Banovich, N. E., García-Pérez, R., Hsiao, C. J., Eres, I. E., Cuevas, C., Marquès‐Bonet, T., & Gilad, Y. (2020) · Genome Research · doi:10.1101/gr.254904.119 · Cited by 131 · see citing works
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Gschwind, A. R., Mualim, K. S., Karbalayghareh, A., Sheth, M. U., Dey, K. K., Jagoda, E., Nurtdinov, R. N., Xi, W., Tan, A. S., Jones, H., et al. (2023) · doi:10.1101/2023.11.09.563812 · Cited by 119 · see citing works
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Hadtstein, F., & Vrolijk, M. F. (2021) · Advances in Nutrition · doi:10.1093/advances/nmab033 · Cited by 120 · see citing works
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Sheikh, A., Md, S., & Kesharwani, P. (2021) · Journal of Controlled Release · doi:10.1016/j.jconrel.2021.10.028 · Cited by 119 · see citing works
He, S., Cheng, J. Q., Sun, L., Wang, Y., Wang, C., Liu, X., Zhang, Z., Zhao, M., Luo, Y., Tian, L., et al. (2018) · Cell Death and Disease · doi:10.1038/s41419-018-0626-6 · Cited by 119 · see citing works
Christensen, N. R., Čalyševa, J., Fernandes, E. F. A., Lüchow, S., Clemmensen, L. S., Haugaard‐Kedström, L. M., & Strømgaard, K. (2019) · Advanced Therapeutics · doi:10.1002/adtp.201800143 · Cited by 110 · see citing works
Morris, J. H., Soman, K., Akbas, R. E., Zhou, X., Smith, B., Meng, E. C., Huang, C. C., Cerono, G., Schenk, G., Rizk-Jackson, A., et al. (2023) · Bioinformatics · doi:10.1093/bioinformatics/btad080 · Cited by 99 · see citing works
Integrative Bioinformatics Analysis for Targeting Hub Genes in Hepatocellular Carcinoma Treatment
Gudivada, I. P., & Amajala, K. C. (2024) · Current Genomics · doi:10.2174/0113892029308243240709073945 · Cited by 100 · see citing works
Zhou, L., Sheng, D., Wang, D., Ma, W., Deng, Q., Deng, L., & Liu, S. (2018) · Cell Biology and Toxicology · doi:10.1007/s10565-018-9444-y · Cited by 99 · see citing works
Li, C., Cai, J.-H., Tsai, J. J. P., & Wang, C. C. N. (2020) · Frontiers in Oncology · doi:10.3389/fonc.2020.00681 · Cited by 97 · see citing works
Naik, B., Kumar, V., Rizwanuddin, S., Chauhan, M., Choudhary, M., Gupta, A. K., Kumar, P., Kumar, V., Saris, P. E. J., Rather, M. A., et al. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms24033025 · Cited by 98 · see citing works
Papier, K., Atkins, J. R., Tong, T. Y. N., Gaitskell, K., Desai, T., Ogamba, C. F., Parsaeian, M., Reeves, G. K., Mills, I. G., Key, T. J., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-48017-6 · Cited by 97 · see citing works
Integrative analyses of the RNA modification machinery reveal tissue- and cancer-specific signatures
Begik, O., Lucas, M. C., Liu, H., Ramírez, J. M., Mattick, J. S., & Novoa, E. M. (2020) · Genome biology · doi:10.1186/s13059-020-02009-z · Cited by 88 · see citing works
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Smith, S. M., & Smith, C. J. (2022) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2022.102427 · Cited by 83 · see citing works
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Shimaoka, M., Kawamoto, E., Gaowa, A., Okamoto, T., & Park, E. J. (2019) · Cancers · doi:10.3390/cancers11010106 · Cited by 81 · see citing works
Targeting receptor complexes: a new dimension in drug discovery
Ishoey, M., Clemmensen, L. S., Bredt, D. S., Bettler, B., & Strømgaard, K. (2020) · Nature Reviews Drug Discovery · doi:10.1038/s41573-020-0086-4 · Cited by 78 · see citing works
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Salokas, K., Öhman, T., Liu, X., Chowdhury, I. M., Gawriyski, L. M., Keskitalo, S., & Varjosalo, M. T. (2022) · EMBO Reports · doi:10.15252/embr.202154041 · Cited by 71 · see citing works
Wu, Y., & Xu, Y. (2020) · Cancer Medicine · doi:10.1002/cam4.2899 · Cited by 75 · see citing works
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Kuang, Z., Liu, X., Zhang, N., Dong, J., Sun, C., Yin, M., Wang, Y., Liu, L., Xiao, D., Zhou, X., et al. (2023) · Cell Death and Differentiation · doi:10.1038/s41418-023-01219-9 · Cited by 75 · see citing works
SARS-CoV-2 uses CD4 to infect T helper lymphocytes
Brunetti, N. S., Davanzo, G. G., de Moraes, D., Ferrari, A., de Souza, G. F., Muraro, S. P., Knittel, T. L., Boldrini, V. D. O., Monteiro, L. D. B., Virgílio-da-Silva, J. V., et al. (2023) · eLife · doi:10.7554/elife.84790 · Cited by 74 · see citing works
Kibinge, N., Relton, C. L., Gaunt, T. R., & Richardson, T. G. (2020) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2020.04.007 · Cited by 68 · see citing works
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Svicher, V., Salpini, R., Piermatteo, L., Carioti, L., Battisti, A., Colagrossi, L., Scutari, R., Surdo, M., Cacciafesta, V., Nuccitelli, A., et al. (2020) · Gut · doi:10.1136/gutjnl-2020-323300 · Cited by 70 · see citing works
Liu, X., Mao, D., Song, Y., Zhu, L., Isak, A. N., Lu, C., Deng, G., Chen, F., Sun, F., Yang, Y. P., et al. (2022) · Science Advances · doi:10.1126/sciadv.abk0133 · Cited by 70 · see citing works
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Xue, Z., Yuan, J., Chen, F., Yao, Y., Xing, S., Yu, X., Li, K., Wang, C., Bao, J., Qu, J., et al. (2022) · EBioMedicine · doi:10.1016/j.ebiom.2022.104161 · Cited by 64 · see citing works
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The era of gene therapy: From preclinical development to clinical application
Alhakamy, N. A., Curiel, D. T., & Berkland, C. J. (2021) · Drug Discovery Today · doi:10.1016/j.drudis.2021.03.021 · Cited by 64 · see citing works
Ferdosi, S., Stukalov, A., Hasan, M., Tangeysh, B., Brown, T. R., Wang, T., Elgierari, E. M., Zhao, X., Huang, Y., Alavi, A., et al. (2022) · Advanced Materials · doi:10.1002/adma.202206008 · Cited by 61 · see citing works
Single cell metabolism: current and future trends
Ali, A., Davidson, S. M., Fraenkel, E., Gilmore, I. S., Hankemeier, T., Kirwan, J., Lane, A. N., Lanekoff, I., Larion, M., McCall, L., et al. (2022) · Metabolomics · doi:10.1007/s11306-022-01934-3 · Cited by 62 · see citing works
Tran, T.-O., Vo, T. H., Lam, L. H. T., & Le, N. Q. K. (2023) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2023.02.045 · Cited by 61 · see citing works
Shen, Y., Liu, J., Zhang, L., Dong, S., Zhang, J., Liu, Y., Zhou, H., & Dong, W. (2019) · BioMed Research International · doi:10.1155/2019/7376034 · Cited by 60 · see citing works
Contribution of upregulated aminoacyl‐tRNA biosynthesis to metabolic dysregulation in gastric cancer
Gao, X., Guo, R. H., Li, Y., Kang, G., Wu, Y. H., Jia, C., Jia, J., Wang, W., Li, Z., Wang, A., et al. (2021) · Journal of Gastroenterology and Hepatology · doi:10.1111/jgh.15592 · Cited by 60 · see citing works
Cheng, T., Wu, Y., Liu, Z., Yu, Y., Sun, S., Guo, M., Sun, B., & Huang, C. L. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.970950 · Cited by 60 · see citing works
López‐Cortés, A., Cabrera‐Andrade, A., Vázquez-Naya, J. M., Pazos, A., González‐Díaz, H., Paz‐y‐Miño, C., Guerrero, S. X., Pérez‐Castillo, Y., Tejera, E., & Munteanu, C. R. (2020) · Scientific Reports · doi:10.1038/s41598-020-65584-y · Cited by 57 · see citing works
Antibodies and methods for immunohistochemistry of extracellular matrix proteins
Rickelt, S., & Hynes, R. O. (2018) · Matrix Biology · doi:10.1016/j.matbio.2018.04.011 · Cited by 51 · see citing works
Song, S., Zhang, M., Xie, P., Wang, S., & Wang, Y. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.978909 · Cited by 52 · see citing works
Plasmon‐Enhanced Single Extracellular Vesicle Analysis for Cholangiocarcinoma Diagnosis
Jeong, M. H., Son, T., Tae, Y. K., Park, C. H., Lee, H. S., Chung, M. J., Park, J. Y., Castro, C. M., Weissleder, R., Jo, J. H., et al. (2023) · Advanced Science · doi:10.1002/advs.202205148 · Cited by 52 · see citing works
Targeting the glutamine-arginine-proline metabolism axis in cancer
Wang, D., Duan, J., Guo, Y., Chen, J., Chen, T.-Q., Wang, J., & Yu, S. (2024) · Journal of Enzyme Inhibition and Medicinal Chemistry · doi:10.1080/14756366.2024.2367129 · Cited by 54 · see citing works
FAM210A is a novel determinant of bone and muscle structure and strength
Tanaka, K.-I., Xue, Y., Nguyen‐Yamamoto, L., Morris, J. A., Kanazawa, I., Sugimoto, T., Wing, S. S., Richards, J. B., & Goltzman, D. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1719089115 · Cited by 51 · see citing works
Machine learning applications in genome-scale metabolic modeling
Kim, Y., Kim, G. B., & Lee, S. Y. (2021) · Current Opinion in Systems Biology · doi:10.1016/j.coisb.2021.03.001 · Cited by 51 · see citing works
Luo, Z., Wang, R., Sun, Y., Liu, J., Chen, Z., & Zhang, Y. (2023) · Briefings in Bioinformatics · doi:10.1093/bib/bbad534 · Cited by 50 · see citing works
Ding, J., Xu, J., Deng, Q., Ma, W., Zhang, R., He, X., Liu, S., & Zhang, L. (2021) · Frontiers in Oncology · doi:10.3389/fonc.2021.722624 · Cited by 49 · see citing works
Potential Therapeutic and Prognostic Values of LSM Family Genes in Breast Cancer
Ta, H. D. K., Wang, W., Phan, N. N., Ton, N. T. A., Anuraga, G., Ku, S., Wu, Y.-F., Wang, C., & Lee, K. (2021) · Cancers · doi:10.3390/cancers13194902 · Cited by 49 · see citing works
Comprehensive proteogenomic characterization of rare kidney tumors
Li, G. X., Chen, L., Hsiao, Y., Mannan, R., Zhang, Y., Luo, J., Petralia, F., Cho, H., Hosseini, N., Leprevost, F. D. V., et al. (2024) · Cell Reports Medicine · doi:10.1016/j.xcrm.2024.101547 · Cited by 48 · see citing works
Non-animal models in dermatological research
Dellambra, E. (2018) · ALTEX · doi:10.14573/altex.1808022 · Cited by 47 · see citing works
Quantitative subcellular reconstruction reveals a lipid mediated inter-organelle biogenesis network
Lee, R. G., Rudler, D. L., Raven, S. A., Peng, L., Chopin, A., Moh, E. S. X., McCubbin, T., Siira, S. J., Fagan, S. V., DeBono, N. J., et al. (2023) · Nature Cell Biology · doi:10.1038/s41556-023-01297-4 · Cited by 47 · see citing works
Shen, Y., Dong, S., Liu, J., Zhang, L., Zhang, J., Zhou, H., & Dong, W. (2020) · BioMed Research International · doi:10.1155/2020/9710421 · Cited by 47 · see citing works
Ma, C., Zhang, H., Rao, Y., Jiang, X., Liu, B., Sun, Z., Song, Z., Gao, Y., Cui, Y., Liu, X., et al. (2025) · npj Digital Medicine · doi:10.1038/s41746-025-02198-6 · Cited by 52 · see citing works
Modhukur, V., Sharma, S., Mondal, M., Lawarde, A., Kask, K., Sharma, R. R., & Salumets, A. (2021) · Cancers · doi:10.3390/cancers13153768 · Cited by 46 · see citing works
Yan, Y., Liang, Q., Xu, Z., Huang, J., Chen, X., Cai, Y., Peng, B., & Yi, Q. (2021) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2021.743046 · Cited by 46 · see citing works
The promise of explainable deep learning for omics data analysis: Adding new discovery tools to AI
Santorsola, M., & Lescai, F. (2023) · New Biotechnology · doi:10.1016/j.nbt.2023.06.002 · Cited by 44 · see citing works
High-Throughput Screening for Drug Discovery
Saxena, S. K. (2021) · IntechOpen eBooks · doi:10.5772/intechopen.91075 · Cited by 46 · see citing works
Behrooz, A. B., Latifi‐Navid, H., Rosa, S. C. D. S., Świat, M., Wiecheć, E., Vitorino, C., Vitorino, R. M. P., Jamalpoor, Z., & Ghavami, S. (2023) · Cancers · doi:10.3390/cancers15123158 · Cited by 44 · see citing works
Protein structure prediction via deep learning: an in-depth review
Meng, Y., Zhang, Z., Zhou, C., Tang, X., Hu, X., Tian, G., Yang, J., & Yao, Y. (2025) · Frontiers in Pharmacology · doi:10.3389/fphar.2025.1498662 · Cited by 49 · see citing works
Li, Z., Lin, Y., Cheng, B., Zhang, Q., & Cai, Y. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2021.571231 · Cited by 44 · see citing works
Sivadasan, P., Gupta, M. K., Sathe, G. J., Sudheendra, H. V., Sunny, S. P., Renu, D., Hari, P., Gowda, H., Suresh, A., Kuriakose, M. A., et al. (2019) · Journal of Proteomics · doi:10.1016/j.jprot.2019.103574 · Cited by 43 · see citing works
Computational methods for protein localization prediction
Jiang, Y., Wang, D., Wang, W., & Xu, D. H. (2021) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2021.10.023 · Cited by 43 · see citing works
Abedini, A., Levinsohn, J. L., Klötzer, K. A., Dumoulin, B., Ma, Z., Frederick, J., Dhillon, P., Balzer, M. S., Shrestha, R., Liu, H., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.10.24.513598 · Cited by 43 · see citing works
Single-Cell Discovery and Multiomic Characterization of Therapeutic Targets in Multiple Myeloma
Yao, L., Wang, J. T., Jayasinghe, R. G., O’Neal, J., Tsai, C., Rettig, M. P., Song, Y., Liu, R., Zhao, Y., Ibrahim, O. M., et al. (2023) · Cancer Research · doi:10.1158/0008-5472.can-22-1769 · Cited by 42 · see citing works
Yang, R., Du, Y., Wang, L., Chen, Z., & Liu, X. (2019) · Journal of Cancer · doi:10.7150/jca.38173 · Cited by 42 · see citing works
Organellar Maps Through Proteomic Profiling – A Conceptual Guide
Borner, G. H. H. (2020) · Molecular & Cellular Proteomics · doi:10.1074/mcp.r120.001971 · Cited by 42 · see citing works
Nakamura, J., Holley, D., Kawamoto, T., & Bultman, S. J. (2020) · Genes and Environment · doi:10.1186/s41021-020-00160-4 · Cited by 42 · see citing works
The clinicomolecular landscape of de novo versus relapsed stage IV metastatic breast cancer
Seltzer, S., Corrigan, M. A., & O’Reilly, S. (2020) · Experimental and Molecular Pathology · doi:10.1016/j.yexmp.2020.104404 · Cited by 41 · see citing works
Chao, C., Yeh, H., Tsai, Y.-T., Chiang, C., & Chen, H. (2020) · Cardiovascular Research · doi:10.1093/cvr/cvaa255 · Cited by 41 · see citing works
Berner, F., Bomze, D., Lichtensteiger, C., Walter, V. P., Niederer, R., Ali, O. H., Wyss, N., Bauer, J., Freudenmann, L. K., Marcu, A., et al. (2022) · Science Immunology · doi:10.1126/sciimmunol.abn9644 · Cited by 40 · see citing works
The Distribution and Role of the CFTR Protein in the Intracellular Compartments
Łukasiak, A., & Zając, M. (2021) · Membranes · doi:10.3390/membranes11110804 · Cited by 42 · see citing works
Arumugam, P., George, R. K., & Priyadharsini, J. V. (2021) · PubMed Central · Cited by 40 · see citing works
TSG101 associates with PARP1 and is essential for PARylation and DNA damage‐induced NF‐κB activation
Tufan, A. B., Lazarow, K., Kolesnichenko, M., Sporbert, A., von Kries, J. P., & Scheidereit, C. (2022) · The EMBO Journal · doi:10.15252/embj.2021110372 · Cited by 38 · see citing works
Mapping diversity in African trypanosomes using high resolution spatial proteomics
Moloney, N. M., Barylyuk, K. V., Tromer, E. C., Crook, O. M., Breckels, L. M., Lilley, K. S., Waller, R. F., & MacGregor, P. (2023) · Nature Communications · doi:10.1038/s41467-023-40125-z · Cited by 40 · see citing works
- Authors
- Thul, P. J., & Lindskog, C.
- Affiliations
- Science for Life Laboratory (SE)
- Uppsala University (SE)
- Corresponding author
- Lindskog, Cecilia
- Venue
- Protein Science
- Publisher
- Wiley
- Published
- 2017-10-10
- Volume
- 27
- Issue
- 1
- Pages
- 233-244
- ISSN
- 0961-8368 (ISSN-L)
- 1469-896X
- PMC
- PMC5734309
- OpenAlex
- W2757254843
- Cited by
- 1,299
- References
- 25
- Citations by year
- 2026: 152 · 2025: 219 · 2024: 239 · 2023: 186 · 2022: 199 · 2021: 151 · 2020: 88 · 2019: 42 · 2018: 22
- FWCI
- 20.65
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Protein Science (publishedVersion, cc-by-nc-nd)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Knut och Alice Wallenbergs Stiftelse
- Topics
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Advanced Biosensing Techniques and Applications
- Keywords
- Human Protein Atlas, human proteome, protein localization, protein expression patterns, immunohistochemistry, immunocytochemistry, spatial proteomics, single-cell gene expression, transcriptomics integration, tissue-specific gene expression
- MeSH terms
- Gene Expression Regulation, Humans, Proteome, Databases, Protein
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