Analysis of the Human Tissue-specific Expression by Genome-wide Integration of Transcriptomics and Antibody-based Proteomics
Open accessAbstract
Global classification of the human proteins with regards to spatial expression patterns across organs and tissues is important for studies of human biology and disease. Here, we used a quantitative transcriptomics analysis (RNA-Seq) to classify the tissue-specific expression of genes across a representative set of all major human organs and tissues and combined this analysis with antibody-based profiling of the same tissues. To present the data, we launch a new version of the Human Protein Atlas that integrates RNA and protein expression data corresponding to ∼80% of the human protein-coding genes with access to the primary data for both the RNA and the protein analysis on an individual gene level. We present a classification of all human protein-coding genes with regards to tissue-specificity and spatial expression pattern. The integrative human expression map can be used as a starting point to explore the molecular constituents of the human body.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
A set of 2,647 genes expressed specifically in brain tissue was strongly enriched for dURVs (OR=1.17; 95% CI=1.11-1.23; P=1.2e-4), whereas sets of genes specific to other tissues, including immune cells, were not.
“We found that a set of 2,647 genes expressed specifically in brain tissue23 was strongly enriched for dURVs (OR=1.17; 95% CI=1.11–1.23; P = 1.2 × 10−4), whereas sets of genes with expression specific to other tissues (including immune cells) were not (Fig. 3a and Supplementary Fig. 7).”
From Increased burden of ultra-rare protein-altering variants among 4,877 individuals with schizophrenia (2016) · cites this paper as [23]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
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
An integrated encyclopedia of DNA elements in the human genome
The ENCODE Project Consortium (2012) · Nature · doi:10.1038/nature11247 · Cited by 18,072 · see citing works
Trapnell, C., Williams, B. A., Pertea, G., Mortazavi, A., Kwan, G., van Baren, M. J., Salzberg, S. L., Wold, B. J., & Pachter, L. (2010) · Nature Biotechnology · doi:10.1038/nbt.1621 · Cited by 15,556 · see citing works
Mapping and quantifying mammalian transcriptomes by RNA-Seq
Mortazavi, A., Williams, B. A., McCue, K., Schaeffer, L., & Wold, B. (2008) · Nature Methods · doi:10.1038/nmeth.1226 · Cited by 13,696 · see citing works
TopHat: discovering splice junctions with RNA-Seq
Trapnell, C., Pachter, L. S., & Salzberg, S. L. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp120 · Cited by 11,477 · 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
A gene atlas of the mouse and human protein-encoding transcriptomes
Su, A. I., Wiltshire, T., Batalov, S., Lapp, H., Ching, K. A., Block, D., Zhang, J., Soden, R., Hayakawa, M., Kreiman, G., et al. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0400782101 · Cited by 3,475 · see citing works
GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists
Eden, E., Navon, R., Steinfeld, I., Lipson, D., & Yakhini, Z. (2009) · BMC Bioinformatics · doi:10.1186/1471-2105-10-48 · Cited by 3,356 · 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
Self-citationUniProt Knowledgebase: a hub of integrated protein data
Magrane, M. (2011) · Database · doi:10.1093/database/bar009 · Cited by 1,455 · see citing works
BioGPS: an extensible and customizable portal for querying and organizing gene annotation resources
Wu, C., Orozco, C., Boyer, J., Leglise, M., Goodale, J., Batalov, S., Hodge, C. L., Haase, J., Janes, J. O., Huss, J. W., et al. (2009) · Genome biology · doi:10.1186/gb-2009-10-11-r130 · Cited by 1,374 · see citing works
NCBI Reference Sequences (RefSeq): current status, new features and genome annotation policy
Pruitt, K. D., Tatusova, T., Brown, G. R., & Maglott, D. R. (2012) · Nucleic Acids Research · doi:10.1093/nar/gkr1079 · Cited by 1,149 · cited 6× · see citing works
“Many well-known genes previously suggested to be tissue-specific were identified as tissue-enriched (supplemental Table S4) in our study, including insulin (pancreas), troponin (heart muscle), protamine (tes- Testis Prostate Ovary Heart muscle Adrenal gland Liver Cerebral cortex Kidney Pancreas Placenta Spleen Stomach…”
BackgroundMethodInfluentialThe Human Protein Atlas—a tool for pathology
Pontén, F., Jirström, K., & Uhlén, M. (2008) · The Journal of Pathology · doi:10.1002/path.2440 · Cited by 1,126 · see citing works
Self-citationDouble indexing overcomes inaccuracies in multiplex sequencing on the Illumina platform
Kircher, M., Sawyer, S., & Meyer, M. (2012) · Nucleic Acids Research · doi:10.1093/nar/gkr771 · Cited by 1,106 · cited 1× · see citing works
“Barcode “Leakage”—As has been previously observed (15) multiplexing of samples on a single lane on the Illumina platform can sometimes lead to misidentification of barcodes, leading to what looks like a cross-contamination between samples.”
BackgroundArrayExpress--a public repository for microarray gene expression data at the EBI
Parkinson, H. (2004) · Nucleic Acids Research · doi:10.1093/nar/gki056 · Cited by 1,075 · see citing works
Flicek, P., Ahmed, I., Amode, M. R., Barrell, D. G., Beal, K. M., Brent, S., Carvalho‐Silva, D., Clapham, P., Coates, G. M. P., Fairley, S., et al. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1236 · Cited by 869 · see citing works
ArrayExpress--a public repository for microarray gene expression data at the EBI
Brāzma, A. (2003) · Nucleic Acids Research · doi:10.1093/nar/gkg091 · Cited by 776 · see citing works
Unique Chromatin Remodeling and Transcriptional Regulation in Spermatogenesis
Sassone‐Corsi, P. (2002) · Science · doi:10.1126/science.1070963 · Cited by 474 · see citing works
Defining the transcriptome and proteome in three functionally different human cell lines
Lundberg, E., Fagerberg, L., Klevebring, D., Matic, I., Geiger, T., Cox, J., Älgenäs, C., Lundeberg, J., Mann, M., & Uhlen, M. (2010) · Molecular Systems Biology · doi:10.1038/msb.2010.106 · Cited by 373 · see citing works
Self-citationRNA sequencing reveals two major classes of gene expression levels in metazoan cells
Hebenstreit, D., Fang, M., Gu, M., Charoensawan, V., van Oudenaarden, A., & Teichmann, S. A. (2011) · Molecular Systems Biology · doi:10.1038/msb.2011.28 · Cited by 289 · see citing works
The chromosome-centric human proteome project for cataloging proteins encoded in the genome
Paik, Y.-K., Jeong, S.-K., Omenn, G. S., Uhlen, M., Hanash, S., Cho, S. Y., Lee, H.-J., Na, K., Choi, E.-Y., Yan, F., et al. (2012) · Nature Biotechnology · doi:10.1038/nbt.2152 · Cited by 288 · see citing works
Self-citationneXtProt: a knowledge platform for human proteins
Lane, L., Argoud‐Puy, G., Britan, A., Cusin, I., Duek, P. D., Evalet, O., Gateau, A., Gaudet, P., Gleizes, A., Masselot, A., et al. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr1179 · Cited by 195 · see citing works
Krupp, M., Marquardt, J. U., Şahin, U., Galle, P. R., Castle, J. C., & Teufel, A. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts084 · Cited by 160 · see citing works
Paavilainen, L., Edvinsson, Å., Asplund, A., Hober, S., Kampf, C., Pontén, F., & Wester, K. (2009) · Journal of Histochemistry & Cytochemistry · doi:10.1369/jhc.2009.954321 · Cited by 142 · see citing works
Self-citationRimm, D. L. (2006) · Nature Biotechnology · doi:10.1038/nbt0806-914 · Cited by 139 · see citing works
Comparison of human solute carriers
Schlessinger, A., Matsson, P., Shima, J. E., Pieper, U., Yee, S. W., Kelly, L., Apeltsin, L., Stroud, R. M., Ferrin, T. E., Giacomini, K. M., et al. (2010) · Protein Science · doi:10.1002/pro.320 · Cited by 111 · see citing works
Antibody-based tissue profiling as a tool for clinical proteomics
Kampf, C., Andersson, A., Wester, K., Björling, E., Uhlén, M., & Pontén, F. (2004) · Clinical Proteomics · doi:10.1385/cp:1:3-4:285 · Cited by 71 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
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
Self-citationO'Leary, N. A., Wright, M. W., Brister, J. R., Ciufo, S., Haddad, D., McVeigh, R., Rajput, B., Robbertse, B., Smith-White, B., Ako-Adjei, D., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkv1189 · Cited by 6,357 · see citing works
“Curation of human genes utilizes analyzed RNA-Seq reads from the Illumina BodyMap 2 (BioProject: PRJEB2445) and Human Protein Atlas projects (BioProject: PRJEB4337) (16).”
MethodMapping genomic loci implicates genes and synaptic biology in schizophrenia
Trubetskoy, V., Pardiñas, A. F., Qi, T., Panagiotaropoulou, G., Awasthi, S., Bigdeli, T. B., Bryois, J., Chen, C.-Y., Dennison, C. A., Hall, L. S., et al. (2022) · Nature · doi:10.1038/s41586-022-04434-5 · Cited by 2,964 · see citing works
Jansen, I. E., Savage, J. E., Watanabe, K., Bryois, J., Williams, D. M., Steinberg, S., Sealock, J., Karlsson, I. K., Hägg, S., Athanasiu, L., et al. (2019) · Nature Genetics · doi:10.1038/s41588-018-0311-9 · Cited by 2,277 · 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
Large-scale integration of the plasma proteome with genetics and disease
Ferkingstad, E., Sulem, P., Atlason, B. A., Sveinbjornsson, G., Magnusson, M. I., Styrmisdottir, E. L., Gunnarsdottir, K., Helgason, A., Oddsson, A., Halldorsson, B. V., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00978-w · Cited by 1,697 · see citing works
The gasdermins, a protein family executing cell death and inflammation
Broz, P., Pelegrín, P., & Shao, F. (2020) · Nature Reviews Immunology · doi:10.1038/s41577-019-0228-2 · Cited by 1,641 · see citing works
GERAD1 Consortium, Pardiñas, A. F., CRESTAR Consortium, Holmans, P., Pocklington, A. J., Escott-Price, V., Ripke, S., Carrera, N., Legge, S. E., Bishop, S., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0059-2 · Cited by 1,552 · see citing works
Database resources of the National Center for Biotechnology Information
Agarwala, R., Barrett, T., Beck, J., Benson, D., Bollin, C., Bolton, E. E., Bourexis, D., Brister, J., Bryant, S. H., Canese, K., et al. (2017) · Nucleic Acids Res. · doi:10.1093/nar/gkx1095 · Cited by 6,277 · see citing works
The human protein atlas: a spatial map of the human proteome
Thul, P. J., & Lindskog, C. (2018) · Protein Science · doi:10.1002/pro.3307 · Cited by 1,299 · see citing works
Strategies for delivering therapeutics across the blood–brain barrier
Terstappen, G. C., Meyer, A. H., Bell, R. D., & Zhang, W. (2021) · Nature Reviews Drug Discovery · doi:10.1038/s41573-021-00139-y · Cited by 1,138 · see citing works
Modelling human development and disease in pluripotent stem-cell-derived gastric organoids
McCracken, K. W., Catá, E. M., Crawford, C. M., Sinagoga, K. L., Schumacher, M., Rockich, B. E., Tsai, Y.-H., Mayhew, C. N., Spence, J. R., Zavros, Y., et al. (2014) · Nature · doi:10.1038/nature13863 · Cited by 980 · see citing works
A deep proteome and transcriptome abundance atlas of 29 healthy human tissues
Wang, D., Eraslan, B., Wieland, T., Hallström, B., Hopf, T., Zolg, D. P., Zecha, J., Asplund, A., Li, L., Meng, C., et al. (2019) · Molecular Systems Biology · doi:10.15252/msb.20188503 · Cited by 750 · see citing works
Self-citationRecent aspects of the effects of zinc on human health
Chasapis, C. T., Ntoupa, P.-S. A., Spiliopoulou, C., & Stefanidou, M. E. (2020) · Archives of Toxicology · doi:10.1007/s00204-020-02702-9 · Cited by 732 · see citing works
Burt, J. B., Demirtaş, M., Eckner, W. J., Navejar, N. M., Ji, J. L., Martin, W. J., Bernacchia, A., Anticevic, A., & Murray, J. D. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0195-0 · Cited by 657 · see citing works
A genome-wide transcriptomic analysis of protein-coding genes in human blood cells
Uhlen, M., Karlsson, M. J., Zhong, W., Tebani, A., Pou, C., Mikes, J., Lakshmikanth, T., Forsström, B., Edfors, F., Odeberg, J., et al. (2019) · Science · doi:10.1126/science.aax9198 · Cited by 594 · see citing works
Self-citationOvercoming therapy resistance in EGFR-mutant lung cancer
Passaro, A., Jänne, P. A., Mok, T., & Peters, S. (2021) · Nature Cancer · doi:10.1038/s43018-021-00195-8 · Cited by 565 · see citing works
Single-Cell Transcriptomics of Regulatory T Cells Reveals Trajectories of Tissue Adaptation
Miragaia, R. J., Gomes, T., Chomka, A., Jardine, L., Riedel, A., Hegazy, A. N., Whibley, N., Tucci, A., Chen, X., Lindeman, I., et al. (2019) · Immunity · doi:10.1016/j.immuni.2019.01.001 · Cited by 499 · see citing works
Evolution to the rescue: using comparative genomics to understand long non-coding RNAs
Ulitsky, I. (2016) · Nature Reviews Genetics · doi:10.1038/nrg.2016.85 · Cited by 533 · see citing works
Predicting multicellular function through multi-layer tissue networks
Žitnik, M., & Leskovec, J. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btx252 · Cited by 515 · see citing works
Increased burden of ultra-rare protein-altering variants among 4,877 individuals with schizophrenia
Genovese, G., Fromer, M., Stahl, E. A., Ruderfer, D. M., Chambert, K., Landén, M., Moran, J. L., Purcell, S. M., Sklar, P., Sullivan, P. F., et al. (2016) · Nature Neuroscience · doi:10.1038/nn.4402 · Cited by 444 · see citing works
Korbecki, J., Kojder, K., Simińska, D., Bohatyrewicz, R., Gutowska, I., Chlubek, D., & Baranowska‐Bosiacka, I. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21218412 · Cited by 469 · see citing works
A benchmark of gene expression tissue-specificity metrics
Kryuchkova-Mostacci, N., & Robinson‐Rechavi, M. (2016) · Briefings in Bioinformatics · doi:10.1093/bib/bbw008 · Cited by 463 · see citing works
Zhou, X., Feliciano, P., Shu, C., Wang, T., Astrovskaya, I., Hall, J. B., Obiajulu, J. U., Wright, J. R., Murali, S. C., Xu, S. X., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01148-2 · Cited by 453 · see citing works
Type III collagen (COL3A1): Gene and protein structure, tissue distribution, and associated diseases
Kuivaniemi, H., & Tromp, G. C. (2019) · Gene · doi:10.1016/j.gene.2019.05.003 · Cited by 431 · see citing works
Bekker‐Jensen, D. B., Martínez‐Val, A., Steigerwald, S., Rüther, P. L., Fort, K. L., Arrey, T. N., Harder, A., Makarov, A., & Olsen, J. V. (2020) · Molecular & Cellular Proteomics · doi:10.1074/mcp.tir119.001906 · Cited by 428 · see citing works
WikiPathways: capturing the full diversity of pathway knowledge
Kutmon, M., Riutta, A., Nunes, N. M., Hanspers, K., Willighagen, E., Bohler, A., Mélius, J., Waagmeester, A., Sinha, S. R., Miller, R. A., et al. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv1024 · Cited by 418 · see citing works
Self‐organized developmental patterning and differentiation in cerebral organoids
Renner, M., Lancaster, M. A., Bian, S., Choi, H., Ku, T., Peer, A., Chung, K., & Knoblich, J. A. (2017) · The EMBO Journal · doi:10.15252/embj.201694700 · Cited by 389 · see citing works
Zinc deficiency and cellular oxidative stress: Prognostic implications in cardiovascular diseases
Choi, S., Liu, X., & Pan, Z. (2018) · Acta Pharmacologica Sinica · doi:10.1038/aps.2018.25 · Cited by 397 · see citing works
Multidimensional proteomics for cell biology
Larance, M., & Lamond, A. I. (2015) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm3970 · Cited by 408 · see citing works
Energy metabolism in health and diseases
Liu, H., Wang, S., Wang, J., Guo, X., Song, Y., Fu, K., Gao, Z., Liu, D., He, W., & Yang, L. (2025) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-025-02141-x · Cited by 438 · see citing works
Sakornsakolpat, P., Prokopenko, D., Lamontagne, M., Reeve, N. F., Guyatt, A. L., Jackson, V. E., Shrine, N. R. G., Qiao, D., Bartz, T. M., Kim, D. K., et al. (2019) · Nature Genetics · doi:10.1038/s41588-018-0342-2 · Cited by 370 · see citing works
Korbecki, J., Grochans, S., Gutowska, I., Barczak, K., & Baranowska‐Bosiacka, I. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21207619 · Cited by 371 · see citing works
Kim, S., Min, S., Choi, Y. S., Jo, S.-H., Jung, J. H., Han, K., Kim, J., An, S., Ji, Y. W., Kim, Y.-G., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-29279-4 · Cited by 375 · see citing works
Walker, L. C., de la Hoya, M., Wiggins, G. A. R., Lindy, A. S., Vincent, L. M., Parsons, M. T., Canson, D. M., Bis‐Brewer, D. M., Cass, A. A., Tchourbanov, A. Y., et al. (2023) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2023.06.002 · Cited by 379 · see citing works
Sequences enriched in Alu repeats drive nuclear localization of long RNAs in human cells
Lubelsky, Y., & Ulitsky, I. (2018) · Nature · doi:10.1038/nature25757 · Cited by 342 · see citing works
Bile acids in glucose metabolism and insulin signalling — mechanisms and research needs
Ahmad, T. R., & Haeusler, R. A. (2019) · Nature Reviews Endocrinology · doi:10.1038/s41574-019-0266-7 · Cited by 342 · see citing works
Systematic Immunotherapy Target Discovery Using Genome-Scale In Vivo CRISPR Screens in CD8 T Cells
Dong, M. B., Wang, G., Chow, R. D., Ye, L., Zhu, L., Dai, X., Park, J. J., Kim, H. R., Errami, Y., Guzman, C. D., et al. (2019) · Cell · doi:10.1016/j.cell.2019.07.044 · Cited by 330 · see citing works
Mehta, M., Dhanjal, D. S., Paudel, K. R., Singh, B., Gupta, G., Rajeshkumar, S., Thangavelu, L. P., Tambuwala, M. M., Bakshi, H. A., Chellappan, D. K., et al. (2020) · Inflammopharmacology · doi:10.1007/s10787-020-00698-3 · Cited by 331 · see citing works
Domains and Functions of Spike Protein in SARS-Cov-2 in the Context of Vaccine Design
Xia, X. (2021) · Viruses · doi:10.3390/v13010109 · Cited by 319 · see citing works
GLP-1 Receptor Expression Within the Human Heart
Baggio, L. L., Yusta, B., Mulvihill, E. E., Cao, X., Streutker, C. J., Butany, J., Cappola, T. P., Margulies, K. B., & Drucker, D. J. (2018) · Endocrinology · doi:10.1210/en.2018-00004 · Cited by 312 · see citing works
Sex differences in severity and mortality from COVID-19: are males more vulnerable?
Pradhan, A., & Olsson, P. (2020) · Biology of Sex Differences · doi:10.1186/s13293-020-00330-7 · Cited by 315 · see citing works
Neuronal timescales are functionally dynamic and shaped by cortical microarchitecture
Gao, R., van den Brink, R. L., Pfeffer, T. A., & Voytek, B. (2020) · eLife · doi:10.7554/elife.61277 · Cited by 293 · see citing works
Houston, B. J., Riera‐Escamilla, A., Wyrwoll, M. J., Salas‐Huetos, A., Xavier, M. J., Nagirnaja, L., Friedrich, C., Conrad, D. F., Aston, K. I., Krausz, C. G., et al. (2021) · Human Reproduction Update · doi:10.1093/humupd/dmab030 · Cited by 287 · see citing works
Chen, W., Yang, A., Jia, J., Popov, Y. V., Schuppan, D., & You, H. (2020) · Hepatology · doi:10.1002/hep.31236 · Cited by 284 · see citing works
Targeting GSK3 and Associated Signaling Pathways Involved in Cancer
Duda, P., Akula, S. M., Abrams, S. L., Steelman, L. S., Martelli, A. M., Cocco, L., Ratti, S., Candido, S., Libra, M., Montalto, G., et al. (2020) · Cells · doi:10.3390/cells9051110 · Cited by 284 · see citing works
Scalise, M., Galluccio, M., Console, L., Pochini, L., & Indiveri, C. (2018) · Frontiers in Chemistry · doi:10.3389/fchem.2018.00243 · Cited by 283 · see citing works
Cysteine metabolic circuitries: druggable targets in cancer
Bonifácio, V. D. B., Pereira, S. A., Serpa, J., & Vicente, J. B. (2020) · British Journal of Cancer · doi:10.1038/s41416-020-01156-1 · Cited by 269 · see citing works
Melatonin in type 2 diabetes mellitus and obesity
Karamitri, A., & Jockers, R. (2019) · Nature Reviews Endocrinology · doi:10.1038/s41574-018-0130-1 · Cited by 268 · see citing works
Sperm defects in primary ciliary dyskinesia and related causes of male infertility
Sironen, A. I., Shoemark, A., Patel, M., Loebinger, M. R., & Mitchison, H. M. (2019) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-019-03389-7 · Cited by 255 · see citing works
The neurobiology of irritable bowel syndrome
Mayer, E. A., Ryu, H. J., & Bhatt, R. R. (2023) · Molecular Psychiatry · doi:10.1038/s41380-023-01972-w · Cited by 285 · see citing works
Múnera, J. O., Sundaram, N., Rankin, S. A., Hill, D. R., Watson, C. L., Mahé, M. M., Vallance, J. E., Shroyer, N. F., Sinagoga, K. L., Zarzoso-Lacoste, A., et al. (2017) · Cell stem cell · doi:10.1016/j.stem.2017.05.020 · Cited by 252 · see citing works
Post-transcriptional regulation across human tissues
Franks, A., Airoldi, E., & Slavov, N. (2017) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1005535 · Cited by 219 · 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 251 · see citing works
Self-citationMiller, A. J., Hill, D. R., Nagy, M. S., Aoki, Y., Dye, B. R., Chin, A. M., Huang, S., Zhu, F., White, E. S., Lama, V. N., et al. (2017) · Stem Cell Reports · doi:10.1016/j.stemcr.2017.11.012 · Cited by 235 · see citing works
Identification of a large set of rare complete human knockouts
Sulem, P., Helgason, H., Oddson, A., Stefansson, H., Gudjonsson, S. A., Zink, F., Hjartarson, E., Sigurdsson, G. T., Jonasdottir, A., Jonasdottir, A., et al. (2015) · Nature Genetics · doi:10.1038/ng.3243 · Cited by 220 · see citing works
Profiling RNA editing in human tissues: towards the inosinome Atlas
Picardi, E., Manzari, C., Mastropasqua, F., Aiello, I., D’Erchia, A. M., & Pesole, G. (2015) · Scientific Reports · doi:10.1038/srep14941 · Cited by 231 · see citing works
Schwenk, J. M., Omenn, G. S., Sun, Z., Campbell, D. S., Baker, M. S., Overall, C. M., Aebersold, R. H., Moritz, R. L., & Deutsch, E. W. (2017) · Journal of Proteome Research · doi:10.1021/acs.jproteome.7b00467 · Cited by 223 · see citing works
Self-citationHot-spot KIF5A mutations cause familial ALS
Brenner, D., Yilmaz, R., Müller, K., Grehl, T., Petri, S., Meyer, T., Großkreutz, J., Weydt, P., Ruf, W. P., Neuwirth, C., et al. (2017) · Brain · doi:10.1093/brain/awx370 · Cited by 228 · see citing works
GSDMB is increased in IBD and regulates epithelial restitution/repair independent of pyroptosis
Rana, N., Privitera, G., Kondolf, H. C., Bulek, K., Lechuga, S., Salvo, C. D., Corridoni, D., Antanaviciute, A., Maywald, R. L., Hurtado, A. M., et al. (2022) · Cell · doi:10.1016/j.cell.2021.12.024 · Cited by 224 · 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
Self-citationFMS-like Tyrosine Kinase 3/FLT3: From Basic Science to Clinical Implications
Kazi, J. U., & Rönnstrand, L. (2019) · Physiological Reviews · doi:10.1152/physrev.00029.2018 · Cited by 216 · see citing works
Estrogen receptor signaling during vertebrate development
Bondesson, M., Hao, R., Lin, C., Williams, C., & Gustafsson, J.-Α. (2014) · Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms · doi:10.1016/j.bbagrm.2014.06.005 · Cited by 209 · see citing works
Recurrent chimeric fusion RNAs in non-cancer tissues and cells
Babiceanu, M., Qin, F., Xie, Z., Jia, Y., Lopez, K., Janus, N., Facemire, L., Kumar, S., Pang, Y., Qi, Y., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw032 · Cited by 202 · see citing works
Epithelial cells activate fibroblasts to promote esophageal cancer development
Chen, Y., Zhu, S., Liu, T., Zhang, S., Lu, J., Fan, W., Lin, L., Xiang, T., Yang, J., Zhao, X., et al. (2023) · Cancer Cell · doi:10.1016/j.ccell.2023.03.001 · Cited by 207 · see citing works
L-Type amino acid transporter 1 as a target for drug delivery
Puris, E., Gynther, M., Auriola, S. O. K., & Huttunen, K. M. (2020) · Pharmaceutical Research · doi:10.1007/s11095-020-02826-8 · Cited by 206 · see citing works
Vujkovic, M., Ramdas, S., Lorenz, K. M., Guo, X., Darlay, R., Cordell, H. J., He, J., Gindin, Y., Chung, C., Myers, R. P., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01078-z · Cited by 205 · see citing works
Self-citationThomas, J. R., Appios, A., Zhao, X., Dutkiewicz, R., Donde, M. J., Lee, C. Y. C., Naidu, P., Lee, C., Cerveira, J., Liu, B., et al. (2020) · The Journal of Experimental Medicine · doi:10.1084/jem.20200891 · Cited by 199 · see citing works
A search for molecular mechanisms underlying male idiopathic infertility
Bracke, A., Peeters, K., Punjabi, U. R., Hoogewijs, D., & Dewilde, S. (2017) · Reproductive BioMedicine Online · doi:10.1016/j.rbmo.2017.12.005 · Cited by 193 · see citing works
Mas-Related G Protein-Coupled Receptor-X2 (MRGPRX2) in Drug Hypersensitivity Reactions
Porębski, G., Kwiecień, K., Pawica, M., & Kwitniewski, M. (2018) · Frontiers in Immunology · doi:10.3389/fimmu.2018.03027 · Cited by 191 · see citing works
The Bgee suite: integrated curated expression atlas and comparative transcriptomics in animals
Bastian, F., Roux, J., Niknejad, A., Comte, A., Costa, S. S. F., de Farias, T. M., Moretti, S., Parmentier, G., de Laval, V. R., Rosikiewicz, M., et al. (2020) · Nucleic Acids Research · doi:10.1093/nar/gkaa793 · Cited by 192 · see citing works
Chen, J., Xu, F., Ruan, X., Sun, J., Zhang, Y., Zhang, H., Zhao, J., Zheng, J., Larsson, S. C., Wang, X., et al. (2023) · EBioMedicine · doi:10.1016/j.ebiom.2023.104494 · Cited by 187 · see citing works
Targeting proprotein convertase subtilisin/kexin type 9 (PCSK9): From bench to bedside
Bao, X., Liang, Y., Chang, H., Cai, T., Feng, B., Gordon, K., Zhu, Y., Shi, H., He, Y., & Xie, L. (2024) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-023-01690-3 · Cited by 187 · see citing works
TISSUES 2.0: an integrative web resource on mammalian tissue expression
Palasca, O., Santos, A., Stolte, C., Gorodkin, J., & Jensen, L. J. (2018) · Database · doi:10.1093/database/bay003 · Cited by 182 · see citing works
Rapid evolution of protein diversity by de novo origination in Oryza
Zhang, L., Ren, Y., Yang, T., Li, G., Chen, J., Gschwend, A. R., Yu, Y., Hou, G., Zi, J., Zhou, R., et al. (2019) · Nature Ecology & Evolution · doi:10.1038/s41559-019-0822-5 · Cited by 184 · see citing works
Transcriptional mediators of treatment resistance in lethal prostate cancer
He, M. X., Cuoco, M. S., Crowdis, J. P., Bosma-Moody, A., Zhang, Z., Bi, K., Kanodia, A., Su, M.-J., Ku, S., Garcia, M. M., et al. (2021) · Nature Medicine · doi:10.1038/s41591-021-01244-6 · Cited by 180 · see citing works
PARPs in lipid metabolism and related diseases
Szántó, M., Gupte, R., Kraus, W. L., Pacher, P., & Bai, P. (2021) · Progress in Lipid Research · doi:10.1016/j.plipres.2021.101117 · Cited by 184 · see citing works
O’Hurley, G., Sjöstedt, E., Rahman, A., Li, B., Kampf, C., Pontén, F., Gallagher, W. M., & Lindskog, C. (2014) · Molecular Oncology · doi:10.1016/j.molonc.2014.03.008 · Cited by 181 · see citing works
Self-citationExome sequencing of Finnish isolates enhances rare-variant association power
Locke, A. E., Steinberg, K. M., Chiang, C. W. K., Service, S. K., Havulinna, A. S., Stell, L., Pirinen, M., Abel, H., Chiang, C., Fulton, R. S., et al. (2019) · Nature · doi:10.1038/s41586-019-1457-z · Cited by 170 · see citing works
Mass Cytometry Imaging for the Study of Human Diseases—Applications and Data Analysis Strategies
Baharlou, H., Canete, N. P., Cunningham, A. L., Harman, A. N., & Patrick, E. (2019) · Frontiers in Immunology · doi:10.3389/fimmu.2019.02657 · Cited by 176 · see citing works
Moffett, J. R., Puthillathu, N., Vengilote, R., Jaworski, D. M., & Namboodiri, A. M. A. (2020) · Frontiers in Physiology · doi:10.3389/fphys.2020.580167 · Cited by 182 · see citing works
A high resolution atlas of gene expression in the domestic sheep (Ovis aries)
Clark, E. L., Bush, S. J., McCulloch, M. E. B., Farquhar, I., Young, R. A., Lefèvre, L., Pridans, C., Tsang, H., Wu, C., Afrasiabi, C., et al. (2017) · PLoS Genetics · doi:10.1371/journal.pgen.1006997 · Cited by 170 · see citing works
Liu, W., Song, J., Du, X., Zhou, Y., Li, Y., Li, R., Lyu, L., He, Y., Hao, J., Ben, J., et al. (2019) · Acta Biomaterialia · doi:10.1016/j.actbio.2019.04.053 · Cited by 174 · see citing works
Common and rare variants associated with kidney stones and biochemical traits
Oddsson, Á., Sulem, P., Helgason, H., Edvardsson, V. O., Þorleifsson, G., Sveinbjörnsson, G., Haraldsdottir, E., Eyjolfsson, G. I., Sigurðardóttir, Ó., Ólafsson, Í., et al. (2015) · Nature Communications · doi:10.1038/ncomms8975 · Cited by 173 · see citing works
Patterns of genic intolerance of rare copy number variation in 59,898 human exomes
Ruderfer, D. M., Hamamsy, T., Lek, M., Karczewski, K. J., Kavanagh, D., Samocha, K. E., Daly, M. J., MacArthur, D. G., Fromer, M., & Purcell, S. (2016) · Nature Genetics · doi:10.1038/ng.3638 · Cited by 164 · see citing works
Growing old, yet staying young: The role of telomeres in bats’ exceptional longevity
Foley, N. M., Hughes, G. M., Huang, Z., Clarke, M., Jebb, D., Whelan, C., PETIT, E. J., Touzalin, F., Farcy, O., Jones, G., et al. (2018) · Science Advances · doi:10.1126/sciadv.aao0926 · Cited by 174 · see citing works
Follicular regulatory T cells produce neuritin to regulate B cells
González-Figueroa, P., Roco, J. A., Papa, I., Núñez-Villacís, L., Stanley, M., Linterman, M. A., Dent, A. L., Cañete, P. F., & Vinuesa, C. G. (2021) · Cell · doi:10.1016/j.cell.2021.02.027 · Cited by 168 · see citing works
Xue, B., Li, H., Guo, M., Wang, J., Xu, Y., Zou, X., Deng, R., Li, G., & Zhu, H. (2018) · Journal of Virology · doi:10.1128/jvi.00321-18 · Cited by 164 · see citing works
Beyond PI3Ks: targeting phosphoinositide kinases in disease
Burke, J. E., Triscott, J., Emerling, B. M., & Hammond, G. R. V. (2023) · Nature Reviews Drug Discovery · doi:10.1038/s41573-022-00582-5 · Cited by 156 · see citing works
Lee, S., Zhang, C., Kiliçarslan, M., Piening, B., Björnson, E., Hallström, B. M., Groen, A. K., Ferrannini, E., Laakso, M., Snyder, M. P., et al. (2016) · Cell Metabolism · doi:10.1016/j.cmet.2016.05.026 · Cited by 163 · see citing works
Self-citationRiyaphan, J., Pham, D., Leong, M. K., & Weng, C. (2021) · Biomolecules · doi:10.3390/biom11121877 · Cited by 176 · see citing works
CARD8 is an inflammasome sensor for HIV-1 protease activity
Wang, Q., Gao, H., Clark, K. M., Mugisha, C. S., Davis, K., Tang, J. P., Harlan, G. H., DeSelm, C. J., Presti, R. M., Kutluay, S. B., et al. (2021) · Science · doi:10.1126/science.abe1707 · Cited by 162 · see citing works
Extreme Genomic CpG Deficiency in SARS-CoV-2 and Evasion of Host Antiviral Defense
Xia, X. (2020) · Molecular Biology and Evolution · doi:10.1093/molbev/msaa094 · Cited by 160 · see citing works
Clinical Implications of SARS-CoV-2 Interaction With Renin Angiotensin System
Brojakowska, A., Narula, J., Shimony, R. Y., & Bander, J. A. (2020) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2020.04.028 · Cited by 156 · see citing works
The Versatile Gasdermin Family: Their Function and Roles in Diseases
Zou, J., Zheng, Y., Huang, Y., Tang, D., Kang, R., & Chen, R. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.751533 · Cited by 151 · see citing works
Ye, J., Wen, Y. F., Sun, X., Chu, X., Li, P., Cheng, B., Cheng, S., Liu, L., Zhang, L., Ma, M., et al. (2020) · Biological Psychiatry · doi:10.1016/j.biopsych.2020.11.019 · Cited by 154 · see citing works
Transcriptomics resources of human tissues and organs
Uhlén, M., Hallström, B. M., Lindskog, C., Mardinoğlu, A., Pontén, F., & Nielsen, J. (2016) · Molecular Systems Biology · doi:10.15252/msb.20155865 · Cited by 144 · see citing works
Self-citationAldehyde Dehydrogenase, Liver Disease and Cancer
Wang, W., Wang, C., Xu, H., & Gao, Y. (2020) · International Journal of Biological Sciences · doi:10.7150/ijbs.42300 · Cited by 150 · see citing works
Saaoud, F., Liu, L., Xu, K., Cueto, R., Shao, Y., Lu, Y., Sun, Y., Snyder, N. W., Wu, S., Yang, L., et al. (2022) · JCI Insight · doi:10.1172/jci.insight.158183 · Cited by 153 · see citing works
- Authors
- Fagerberg, L., Hallström, B. M., Oksvold, P., Kampf, C., Djureinovic, D., Odeberg, J., Habuka, M., Tahmasebpoor, S., Danielsson, A., Edlund, K., Asplund, A., Sjöstedt, E., Lundberg, E., Szigyarto, C. A.-K., Skogs, M., Takanen, J. O., Berling, H., Tegel, H., Mulder, J., Nilsson, P., Schwenk, J. M., Lindskog, C., Danielsson, F., Mardinoglu, A., Sivertsson, Å., von Feilitzen, K., Forsberg, M., Zwahlen, M., Olsson, I., Navani, S., Huss, M., Nielsen, J., Ponten, F., & Uhlén, M.
- Affiliations
- Science for Life Laboratory (SE)
- Uppsala University (SE)
- KTH Royal Institute of Technology (SE)
- Corresponding author
- Uhlén, Mathias
- ORCID
- Venue
- Molecular & Cellular Proteomics
- Publisher
- Elsevier BV
- Published
- 2014-02
- Volume
- 13
- Issue
- 2
- Pages
- 397-406
- ISSN
- 1535-9476 (ISSN-L)
- PMC
- PMC3916642
- OpenAlex
- W2167898988
- Cited by
- 3,665
- References
- 28
- Citations by year
- 2026: 163 · 2025: 292 · 2024: 458 · 2023: 422 · 2022: 438 · 2021: 474 · 2020: 528 · 2019: 387 · 2018: 255 · 2017: 105 · 2016: 43 · 2015: 64 · 2014: 28
- FWCI
- 20.19
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Molecular & Cellular Proteomics (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Chalmers Research (Chalmers University of Technology) (submittedVersion)
- Chalmers Publication Library (Chalmers University of Technology) (submittedVersion)
- Funders
- Knut och Alice Wallenbergs Stiftelse
- Science for Life Laboratory
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Keywords
- tissue-specific gene expression, spatial expression patterns, Human Protein Atlas, RNA-seq, antibody-based proteomics, protein-coding genes, human organs, gene expression atlas
- MeSH terms
- Antibodies, Female, Humans, Male, Organ Specificity, Proteins, Gene Expression, Systems Integration, Proteome, Gene Expression Profiling, Genomics, Proteomics, Tissue Array Analysis, Gene Regulatory Networks, Transcriptome
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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review