Human Protein Atlas

Human Protein Atlas
Content
Description	The Human Protein Atlas portal is a publicly available database with millions of high-resolution images showing the spatial distribution of proteins in normal human tissues and different cancer types, as well the sub cellular localisation in single cells.
Organisms	Human
Contact
Research center	KTH, UU, SciLifeLab, Sweden
Primary citation	Uhlén M, et al. (January 2015). "Proteomics. Tissue-based map of the human proteome". Science. 347 (6220): 1260419. doi:10.1126/science.1260419. PMID 25613900. S2CID 802377.
Access
Website	www.proteinatlas.org
Download URL	www.proteinatlas.org/about/download
Tools
Web	Advanced search, bulk retrieval/download
Miscellaneous
Versioning	Yes
Data release; frequency	12 months
Version	23
Curation policy	Yes – manual
Bookmarkable; entities	Yes – both individual protein entries and searches

Last updated November 21, 2023

The Human Protein Atlas (HPA) is a Swedish-based program started in 2003 with the aim to map all the human proteins in cells, tissues and organs using integration of various omics technologies, including antibody-based imaging, mass spectrometry-based proteomics, transcriptomics and systems biology. All the data in the knowledge resource is open access to allow scientists both in academia and industry to freely access the data for exploration of the human proteome. In June 2023, version 23 was launched where a new Interaction section was introduced containing human protein-protein interaction networks for more than 11,000 genes that will add new aspects in terms of protein function.

The resource now includes twelve separate sections with complementary information about all human proteins. All data has been updated on the approximately 5 million individual web pages. The Human Protein Atlas program has already contributed to several thousands of publications in the field of human biology and disease and was selected by the organization ELIXIR as a European core resource due to its fundamental importance for a wider life science community. The HPA consortium is funded by the Knut and Alice Wallenberg Foundation.

Twelve sections

The Human Protein Atlas consists of twelve sections:

The Tissue^[1] section of the Human Protein Atlas focuses on the expression profiles in human tissues of genes both on the mRNA and protein level. The protein expression data from 44 normal human tissue types is derived from antibody-based protein profiling using conventional and multiplex immunohistochemistry. All underlying images of immunohistochemistry stained normal tissues are available together with knowledge-based annotation of protein expression levels.
The Brain^[2] section provides comprehensive spatial profiling of the brain, including overview of protein expression in the mammalian brain based on integration of data from human, pig and mouse. Transcriptomics data combined with affinity-based protein in situ localization down to single cell detail is available in this brain-centric sub atlas of the Human Protein Atlas. The data presented are for human genes and their one-to-one orthologues in pig and mouse. Gene summary pages provide the hierarchical expression landscape form 13 main regions of the brain to individual nuclei and subfields for every protein coding gene. For selected proteins, high content images are available to explore the cellular and subcellular protein distribution. In addition, the Brain section contains lists of genes with elevated expression in one or a group of regions to help the user identify unique protein expression profiles linked to physiology and function.
The Single Cell Type^[3] section contains information based on single cell RNA sequencing (scRNAseq) data from 31 human tissues including peripheral blood mononuclear cells (PBMCs). The data is linked to in-house generated immunohistochemically stained tissue sections presented in the Tissue section in order to visualize the corresponding spatial protein expression patterns. The scRNAseq analysis was based on publicly available genome-wide expression data and comprises all protein-coding genes in 557 individual cell type clusters corresponding to 15 different cell type groups. A specificity classification was performed to determine the number of genes elevated in these single cell types. The genes expressed in each of the cell types can be explored in interactive UMAP plots and bar charts, with links to corresponding immunohistochemical stainings in human tissues.
The Tissue Cell Type section contains cell type expression specificity predictions for all human protein coding genes, generated using integrated network analysis of publicly available bulk RNAseq data. A specificity classification is used to predict which genes are enriched in each constituent cell type within an individual tissue. The data can be explored on a tissue-by-tissue basis, together with in-house generated immunohistochemically stained tissue sections. In addition, a core cell type analysis focuses on the cell types found in all, or the majority, of the profiled tissues, e.g., endothelial cells or macrophages. Here, genes with predicted specificity in these core cell types in multiple tissues are detailed.
The Pathology^[4] section contains information based on mRNA and protein expression data from 17 different forms of human cancer, together with millions of in-house generated immunohistochemically stained tissue sections images and Kaplan-Meier plots showing the correlation between mRNA expression of each human protein gene and cancer patient survival.
The Disease section contains information on protein levels in blood in patients with different diseases and highlights proteins associated with these diseases using differential expression analysis and a disease prediction strategy based on machine-learning.
The Immune Cell^[5] section contains single cell information on genome-wide RNA expression profiles of human protein-coding genes covering various B- and T-cells, monocytes, granulocytes and dendritic cells. The transcriptomics analysis covers 18 cell types isolated with cell sorting and includes classification based on specificity, distribution and expression cluster across all immune cells.
The Blood Protein^[6] section presents estimated plasma concentrations of the proteins detected in human blood from mass spectrometry-based proteomics studies, published immune assay data and a longitudinal study based on proximity extension assay (PEA). Further, an analysis of the “human secretome” is presented including annotation of the genes predicted to be actively secreted to human blood, as well as to other compartments or organ systems of the human body such as the digestive tract or the brain.
The Subcellular^[7] section of the Human Protein Atlas provides high-resolution insights into the expression and spatiotemporal distribution of proteins encoded by 13147 genes (65% of the human protein-coding genes). For each gene, the subcellular distribution of the protein has been investigated by immunofluorescence (ICC-IF) and confocal microscopy in up to three different cell lines, selected from a panel of 37 cell lines used in the subcellular section. Upon image analysis, the subcellular localization of the protein has been classified into one or more of 35 different organelles and fine subcellular structures. In addition, the section includes an annotation of genes that display single-cell variation in protein expression levels and/or subcellular distribution, as well as an extended analysis of cell cycle dependency of such variations.
The Cell Line section contains information on genome-wide RNA expression profiles of human protein-coding genes in 1206 human cell lines, including 1132 cancer cell lines. The transcriptomics analysis includes classification based on specificity analysis across 28 cancer types, distribution and expression cluster analysis across all cell lines and for selected cancer types also analysis of similarity of the cell lines to their corresponding cancer type.
The Structure section contains information about the three-dimensional structure of human proteins.
The Interaction section presents data on interaction networks based on protein-protein interactions from the IntAct database^[8] and metabolic pathways from the Metabolic Atlas.^[9]

Additional features

In addition to the twelve sections of HPA, exploring gene and protein expression, there are various features available at the HPA website to assist the research community, including integrated external resources, such as Metabolic Atlas, educational material and free downloadable data.

The “Learn” section of HPA includes educational resources, including information regarding antibody-based applications and techniques, a histology dictionary and educational 3D videos. The dictionary is an interactive tool for free full-screen exploration of whole slide images of normal human organs and tissues, cancer tissues and cell structures, guided with detailed annotations of all major structural elements. Educational videos have been produced by HPA, depicting the exploration of the human body in 3D, using antibody-based profiling of tissues and light sheet microscopy. The movies are available at the HPA website as well as on a YouTube channel.
Datasets used in HPA are made freely available to encourage further studies within the research community. Access to the extensive datasets is given through the downloadable data page of HPA, wherein 29 different downloadable files are available, containing genome‐wide data across various assays.

History

The Human Protein Atlas program was started in 2003 and funded by the non-profit organization Knut and Alice Wallenberg Foundation (KAW). The main site of the project is the Royal Institute of Technology (KTH), School of Engineering Sciences in Chemistry, Biotechnology and Health (Stockholm, Sweden). Additionally, the project involves research groups at Uppsala University, Karolinska Institutet, Chalmers University of Technology and Lund University, as well as several present and past international collaborations initiated with research groups in Europe, the United States, South Korea, China, and India. Professor Mathias Uhlén is the director of the program.

The research underpinning the start of the exploration of the whole human proteome in the Human Protein Atlas program was carried out in the late 1990s and early 2000s. A pilot study employing an affinity proteomics strategy using affinity-purified antibodies raised against recombinant human protein fragments was carried out for a chromosome-wide protein profiling of chromosome 21.^[10] Other projects were also carried out to establish processes for parallel and automated affinity purification of mono-specific antibodies and their validation.^[11]^[12]

Research

Antibodies and antigens, produced in the Human Protein Atlas workflow, are used in research projects to study potential biomarkers in various diseases, such as breast cancer, prostate cancer, colon cancer, diabetes, autoimmune diseases, ovarian cancer and renal failure.^[13]^[14]^[15]^[16]^[17]^[18]

Researchers involved with Human Protein Atlas projects, are sharing protocols and method details in an open-access group on protocols.io.^[19] A large effort is put into validating the antibody reagents used for profiling of tissues and cells, and the HPA has implemented stringent antibody validation criteria as suggested by the International Working Group for Antibody Validation (IWGAV).^[20]^[21]^[22]

Collaborations

The Human Protein Atlas program has participated in 9 EU research projects ENGAGE, PROSPECTS, BIO_NMD, AFFINOMICS, CAGEKID, EURATRANS, ITFoM, DIRECT and PRIMES.

Related Research Articles

The endometrium is the inner epithelial layer, along with its mucous membrane, of the mammalian uterus. It has a basal layer and a functional layer: the basal layer contains stem cells which regenerate the functional layer. The functional layer thickens and then is shed during menstruation in humans and some other mammals, including apes, Old World monkeys, some species of bat, the elephant shrew and the Cairo spiny mouse. In most other mammals, the endometrium is reabsorbed in the estrous cycle. During pregnancy, the glands and blood vessels in the endometrium further increase in size and number. Vascular spaces fuse and become interconnected, forming the placenta, which supplies oxygen and nutrition to the embryo and fetus. The speculated presence of an endometrial microbiota has been argued against.

The duodenum is the first section of the small intestine in most higher vertebrates, including mammals, reptiles, and birds. In mammals it may be the principal site for iron absorption. The duodenum precedes the jejunum and ileum and is the shortest part of the small intestine.

Immunohistochemistry (IHC) is the most common application of immunostaining. It involves the process of selectively identifying antigens (proteins) in cells of a tissue section by exploiting the principle of antibodies binding specifically to antigens in biological tissues. IHC takes its name from the roots "immuno", in reference to antibodies used in the procedure, and "histo", meaning tissue. Albert Coons conceptualized and first implemented the procedure in 1941.

Caspase 14 is an enzyme that in humans is encoded by the CASP14 gene.

Receptor expression-enhancing protein 2 is a protein that in humans is encoded by the REEP2 gene.

Special AT-rich sequence-binding protein 2 (SATB2) also known as DNA-binding protein SATB2 is a protein that in humans is encoded by the SATB2 gene. SATB2 is a DNA-binding protein that specifically binds nuclear matrix attachment regions and is involved in transcriptional regulation and chromatin remodeling. SATB2 shows a restricted mode of expression and is expressed in certain cell nuclei. The SATB2 protein is mainly expressed in the epithelial cells of the colon and rectum, followed by the nuclei of neurons in the brain.

Cubilin is a protein that in humans is encoded by the CUBN gene.

The Human Proteome Project (HPP) is a collaborative effort coordinated by the Human Proteome Organization. Its stated goal is to experimentally observe all of the proteins produced by the sequences translated from the human genome.

The secretome is the set of proteins expressed by an organism and secreted into the extracellular space. In humans, this subset of the proteome encompasses 13-20% of all proteins, including cytokines, growth factors, extracellular matrix proteins and regulators, and shed receptors. The secretome of a specific tissue can be measured by mass spectrometry and its analysis constitutes a type of proteomics known as secretomics.

CXorf66 also known as Chromosome X Open Reading Frame 66, is a 361aa protein in humans that is encoded by the CXorf66 gene. The protein encoded is predicted to be a type 1 transmembrane protein; however, its exact function is currently unknown.

KIAA0825 is a protein that in humans is encoded by the gene of the same name, located on chromosome 5, 5q15. It is a possible risk factor in Type II Diabetes, and associated with high levels of glucose in the blood. It is a relatively fast mutating gene, compared to other coding genes. There is however one region which is highly conserved across the species that have the gene, known as DUF4495. It is predicted to travel between the nucleus and the cytoplasm.

Mathias Uhlén is a Swedish scientist and Professor of Microbiology at Royal Institute of Technology (KTH), Stockholm. After a post-doc period at the EMBL in Heidelberg, Germany, he became professor in microbiology at KTH in 1988. His research is focused on protein science, antibody engineering and precision medicine and range from basic research in human and microbial biology to more applied research, including clinical applications. He is member of several academies and societies, including Royal Swedish Academy of Science (KVA), National Academy of Engineering (NAE) and the Swedish Academy of Engineering Science (IVA). Dr Uhlen was the Founding Director of the national infrastructure Science for Life Laboratory (SciLifeLab) from 2010-2015

SHLD1 or shieldin complex subunit 1 is a gene on chromosome 20. The C20orf196 gene encodes an mRNA that is 1,763 base pairs long, and a protein that is 205 amino acids long.

Chromosome 1 open reading frame 112, is a protein that in humans is encoded by the C1orf112 gene, and is located at position 1q24.2. C1orf112 encodes for seventeen variants of mRNA, fifteen of which are functional proteins. C1orf112 has a determined precursor molecular weight of 96.6 kDa and an isoelectric point of 5.62. C1orf112 has been experimentally determined to localize to the mitochondria, although it does not contain a mitochondrial targeting sequence.

LOC101928193 is a protein which in humans is encoded by the LOC101928193 gene. There are no known aliases for this gene or protein. Similar copies of this gene, called orthologs, are known to exist in several different species across mammals, amphibians, fish, mollusks, cnidarians, fungi, and bacteria. The human LOC101928193 gene is located on the long (q) arm of chromosome 9 with a cytogenic location at 9q34.2. The molecular location of the gene is from base pair 133,189,767 to base pair 133,192,979 on chromosome 9 for an mRNA length of 3213 nucleotides. The gene and protein are not yet well understood by the scientific community, but there is data on its genetic makeup and expression. The LOC101928193 protein is targeted for the cytoplasm and has the highest level of expression in the thyroid, ovary, skin, and testes in humans.

Glutamate-rich protein 4 is encoded by the gene ERICH4 and can be otherwise known as chromosome 19 open reading frame 69 (C19orf69). ERICH4 is highly conserved in mammals and exhibits overexpression in tissues of the kidneys, terminal ileum, and duodenum. The function of ERICH4 has yet to be well understood by the scientific community but is suggested to contribute to immune inflammatory responses.

RTP3 is a gene located on chromosome 3 in humans that encodes the RTP3 protein. Its expression is liver-restricted.

Chromosome 12 Open Reading Frame 50 (C12orf50) is a protein-encoding gene which in humans encodes for the C12orf50 protein. The accession id for this gene is NM_152589. The location of C12orf50 is 12q21.32. It covers 55.42 kb, from 88429231 to 88373811, on the reverse strand. Some of the neighboring genes to C12orf50 are RPS4XP15, LOC107984542, and C12orf29. RPS4XP15 is upstream C12orf50 and is on the same strand. LOC107984542 and C12orf29 are both downstream. LOC107984542 is on the opposite strand while C12orf29 is on the same strand. C12orf50 has six isoforms. This page is focusing on isoform X1. C12orf50 isoform X1 is 1711 nucleotides long and has a protein with a length of 414 aa.

CCDC188 or coiled-coil domain containing protein is a protein that in humans is encoded by the CCDC188 gene.

FAM131A is a protein that is encoded by the FAM131A gene in humans. Aliases for FAM131A include C3orf40, FLAT715, and PRO1378.

References

Text was copied from The Human Protein Atlas, which is available under a Creative Commons Attribution-ShareAlike 3.0 Unported license.

↑ Uhlén M, Fagerberg L, Hallström BM, Lindskog C, Oksvold P, Mardinoglu A, et al. (January 2015). "Proteomics. Tissue-based map of the human proteome". Science. 347 (6220): 1260419. doi:10.1126/science.1260419. PMID 25613900. S2CID 802377.
↑ Sjöstedt, E; Zhong, W; Fagerberg, L; Karlsson, M; Mitsios, N; Adori, C; Oksvold, P; Edfors, F; Limiszewska, A; Hikmet, F; Huang, J; Du, Y; Lin, L; Dong, Z; Yang, L; Liu, X; Jiang, H; Xu, X; Wang, J; Yang, H; Bolund, L; Mardinoglu, A; Zhang, C; von Feilitzen, K; Lindskog, C; Pontén, F; Luo, Y; Hökfelt, T; Uhlén, M; Mulder, J (2020). "An atlas of the protein-coding genes in the human, pig, and mouse brain". Science. 367 (6482). doi:10.1126/science.aay5947. PMID 32139519. S2CID 212560645.
↑ Karlsson, M; Zhang, C; Méar, L; Zhong, W; Digre, A; Katona, B; Sjöstedt, E; Butler, L; Odeberg, J; Dusart, P; Edfors, F; Oksvold, P; von Feilitzen, K; Zwahlen, M; Arif, M; Altay, O; Li, X; Ozcan, M; Mardinoglu, A; Fagerberg, L; Mulder, J; Luo, Y; Ponten, F; Uhlén, M; Lindskog, C (July 2021). "A single-cell type transcriptomics map of human tissues". Science Advances. 7 (31). Bibcode:2021SciA....7.2169K. doi:10.1126/sciadv.abh2169. PMC 8318366 . PMID 34321199.
↑ Uhlen, M; Zhang, C; Lee, S; Sjöstedt, E; Fagerberg, L; Bidkhori, G; Benfeitas, R; Arif, M; Liu, Z; Edfors, F; Sanli, K; von Feilitzen, K; Oksvold, P; Lundberg, E; Hober, S; Nilsson, P; Mattsson, J; Schwenk, JM; Brunnström, H; Glimelius, B; Sjöblom, T; Edqvist, PH; Djureinovic, D; Micke, P; Lindskog, C; Mardinoglu, A; Ponten, F (18 August 2017). "A pathology atlas of the human cancer transcriptome". Science. 357 (6352). doi: 10.1126/science.aan2507 . PMID 28818916. S2CID 206659235.
↑ Uhlen, M; Karlsson, MJ; Zhong, W; Tebani, A; Pou, C; Mikes, J; Lakshmikanth, T; Forsström, B; Edfors, F; Odeberg, J; Mardinoglu, A; Zhang, C; von Feilitzen, K; Mulder, J; Sjöstedt, E; Hober, A; Oksvold, P; Zwahlen, M; Ponten, F; Lindskog, C; Sivertsson, Å; Fagerberg, L; Brodin, P (20 December 2019). "A genome-wide transcriptomic analysis of protein-coding genes in human blood cells". Science. 366 (6472). doi:10.1126/science.aax9198. PMID 31857451. S2CID 209424418.
↑ Uhlén, M; Karlsson, MJ; Hober, A; Svensson, AS; Scheffel, J; Kotol, D; Zhong, W; Tebani, A; Strandberg, L; Edfors, F; Sjöstedt, E; Mulder, J; Mardinoglu, A; Berling, A; Ekblad, S; Dannemeyer, M; Kanje, S; Rockberg, J; Lundqvist, M; Malm, M; Volk, AL; Nilsson, P; Månberg, A; Dodig-Crnkovic, T; Pin, E; Zwahlen, M; Oksvold, P; von Feilitzen, K; Häussler, RS; Hong, MG; Lindskog, C; Ponten, F; Katona, B; Vuu, J; Lindström, E; Nielsen, J; Robinson, J; Ayoglu, B; Mahdessian, D; Sullivan, D; Thul, P; Danielsson, F; Stadler, C; Lundberg, E; Bergström, G; Gummesson, A; Voldborg, BG; Tegel, H; Hober, S; Forsström, B; Schwenk, JM; Fagerberg, L; Sivertsson, Å (26 November 2019). "The human secretome". Science Signaling. 12 (609). doi: 10.1126/scisignal.aaz0274 . PMID 31772123. S2CID 208321549.
↑ Thul, PJ; Åkesson, L; Wiking, M; Mahdessian, D; Geladaki, A; Ait Blal, H; Alm, T; Asplund, A; Björk, L; Breckels, LM; Bäckström, A; Danielsson, F; Fagerberg, L; Fall, J; Gatto, L; Gnann, C; Hober, S; Hjelmare, M; Johansson, F; Lee, S; Lindskog, C; Mulder, J; Mulvey, CM; Nilsson, P; Oksvold, P; Rockberg, J; Schutten, R; Schwenk, JM; Sivertsson, Å; Sjöstedt, E; Skogs, M; Stadler, C; Sullivan, DP; Tegel, H; Winsnes, C; Zhang, C; Zwahlen, M; Mardinoglu, A; Pontén, F; von Feilitzen, K; Lilley, KS; Uhlén, M; Lundberg, E (26 May 2017). "A subcellular map of the human proteome". Science. 356 (6340). doi:10.1126/science.aal3321. PMID 28495876. S2CID 10744558.
↑ Orchard, S; Ammari, M; Aranda, B; Breuza, L; Briganti, L; Broackes-Carter, F; Campbell, NH; Chavali, G; Chen, C; del-Toro, N; Duesbury, M; Dumousseau, M; Galeota, E; Hinz, U; Iannuccelli, M; Jagannathan, S; Jimenez, R; Khadake, J; Lagreid, A; Licata, L; Lovering, RC; Meldal, B; Melidoni, AN; Milagros, M; Peluso, D; Perfetto, L; Porras, P; Raghunath, A; Ricard-Blum, S; Roechert, B; Stutz, A; Tognolli, M; van Roey, K; Cesareni, G; Hermjakob, H (January 2014). "The MIntAct project--IntAct as a common curation platform for 11 molecular interaction databases". Nucleic Acids Research. 42 (Database issue): D358-63. doi:10.1093/nar/gkt1115. PMC 3965093 . PMID 24234451.
↑ Robinson, JL; Kocabaş, P; Wang, H; Cholley, PE; Cook, D; Nilsson, A; Anton, M; Ferreira, R; Domenzain, I; Billa, V; Limeta, A; Hedin, A; Gustafsson, J; Kerkhoven, EJ; Svensson, LT; Palsson, BO; Mardinoglu, A; Hansson, L; Uhlén, M; Nielsen, J (24 March 2020). "An atlas of human metabolism". Science Signaling. 13 (624). doi:10.1126/scisignal.aaz1482. PMC 7331181 . PMID 32209698.
↑ Agaton C, Galli J, Höidén Guthenberg I, Janzon L, Hansson M, Asplund A, Brundell E, Lindberg S, Ruthberg I, Wester K, Wurtz D, Höög C, Lundeberg J, Ståhl S, Pontén F, Uhlén M (Jun 2003). "Affinity proteomics for systematic protein profiling of chromosome 21 gene products in human tissues". Molecular & Cellular Proteomics. 2 (6): 405–14. doi: 10.1074/mcp.M300022-MCP200 . PMID 12796447.
↑ Falk R, Agaton C, Kiesler E, Jin S, Wieslander L, Visa N, Hober S, Ståhl S (Dec 2003). "An improved dual-expression concept, generating high-quality antibodies for proteomics research". Biotechnology and Applied Biochemistry. 38 (Pt 3): 231–9. doi:10.1042/BA20030091. PMID 12875650. S2CID 43820440.
↑ Uhlén M, Björling E, Agaton C, Szigyarto CA, Amini B, Andersen E, et al. (Dec 2005). "A human protein atlas for normal and cancer tissues based on antibody proteomics". Molecular & Cellular Proteomics. 4 (12): 1920–32. doi: 10.1074/mcp.M500279-MCP200 . PMID 16127175.
↑ Jonsson L, Gaber A, Ulmert D, Uhlén M, Bjartell A, Jirström K (2011). "High RBM3 expression in prostate cancer independently predicts a reduced risk of biochemical recurrence and disease progression". Diagnostic Pathology. 6: 91. doi: 10.1186/1746-1596-6-91 . PMC 3195697 . PMID 21955582.
↑ Larsson A, Fridberg M, Gaber A, Nodin B, Levéen P, Jönsson G, Uhlén M, Birgisson H, Jirström K (2012). "Validation of podocalyxin-like protein as a biomarker of poor prognosis in colorectal cancer". BMC Cancer. 12: 282. doi: 10.1186/1471-2407-12-282 . PMC 3492217 . PMID 22769594.
↑ Lindskog C, Asplund A, Engkvist M, Uhlen M, Korsgren O, Ponten F (Jun 2010). "Antibody-based proteomics for discovery and exploration of proteins expressed in pancreatic islets". Discovery Medicine. 9 (49): 565–78. PMID 20587347.
↑ Neiman M, Hedberg JJ, Dönnes PR, Schuppe-Koistinen I, Hanschke S, Schindler R, Uhlén M, Schwenk JM, Nilsson P (Nov 2011). "Plasma profiling reveals human fibulin-1 as candidate marker for renal impairment". Journal of Proteome Research. 10 (11): 4925–34. doi:10.1021/pr200286c. PMID 21888404.
↑ Nodin B, Fridberg M, Jonsson L, Bergman J, Uhlén M, Jirström K (2012). "High MCM3 expression is an independent biomarker of poor prognosis and correlates with reduced RBM3 expression in a prospective cohort of malignant melanoma". Diagnostic Pathology. 7: 82. doi: 10.1186/1746-1596-7-82 . PMC 3433373 . PMID 22805320.
↑ Schwenk JM, Igel U, Neiman M, Langen H, Becker C, Bjartell A, Ponten F, Wiklund F, Grönberg H, Nilsson P, Uhlen M (Nov 2010). "Toward next generation plasma profiling via heat-induced epitope retrieval and array-based assays". Molecular & Cellular Proteomics. 9 (11): 2497–507. doi:10.1074/mcp.M110.001560. PMC 2984230 . PMID 20682762.
↑ "Human Protein Atlas - research group on protocols.io". protocols.io. Retrieved 2019-12-12.
↑ Uhlen, M; Bandrowski, A; Carr, S; Edwards, A; Ellenberg, J; Lundberg, E; Rimm, DL; Rodriguez, H; Hiltke, T; Snyder, M; Yamamoto, T (October 2016). "A proposal for validation of antibodies". Nature Methods. 13 (10): 823–7. doi:10.1038/nmeth.3995. PMC 10335836 . PMID 27595404. S2CID 34259132.
↑ Edfors, F; Hober, A; Linderbäck, K; Maddalo, G; Azimi, A; Sivertsson, Å; Tegel, H; Hober, S; Szigyarto, CA; Fagerberg, L; von Feilitzen, K; Oksvold, P; Lindskog, C; Forsström, B; Uhlen, M (8 October 2018). "Enhanced validation of antibodies for research applications". Nature Communications. 9 (1): 4130. Bibcode:2018NatCo...9.4130E. doi:10.1038/s41467-018-06642-y. PMC 6175901 . PMID 30297845.
↑ Sivertsson, Å; Lindström, E; Oksvold, P; Katona, B; Hikmet, F; Vuu, J; Gustavsson, J; Sjöstedt, E; von Feilitzen, K; Kampf, C; Schwenk, JM; Uhlén, M; Lindskog, C (10 November 2020). "Enhanced Validation of Antibodies Enables the Discovery of Missing Proteins". Journal of Proteome Research. 19 (12): 4766–4781. doi:10.1021/acs.jproteome.0c00486. PMC 7723238 . PMID 33170010.

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[1] Uhlén M, Fagerberg L, Hallström BM, Lindskog C, Oksvold P, Mardinoglu A, et al. (January 2015). "Proteomics. Tissue-based map of the human proteome". Science. 347 (6220): 1260419. doi:10.1126/science.1260419. PMID 25613900. S2CID 802377.

[2] Sjöstedt, E; Zhong, W; Fagerberg, L; Karlsson, M; Mitsios, N; Adori, C; Oksvold, P; Edfors, F; Limiszewska, A; Hikmet, F; Huang, J; Du, Y; Lin, L; Dong, Z; Yang, L; Liu, X; Jiang, H; Xu, X; Wang, J; Yang, H; Bolund, L; Mardinoglu, A; Zhang, C; von Feilitzen, K; Lindskog, C; Pontén, F; Luo, Y; Hökfelt, T; Uhlén, M; Mulder, J (2020). "An atlas of the protein-coding genes in the human, pig, and mouse brain". Science. 367 (6482). doi:10.1126/science.aay5947. PMID 32139519. S2CID 212560645.

[3] Karlsson, M; Zhang, C; Méar, L; Zhong, W; Digre, A; Katona, B; Sjöstedt, E; Butler, L; Odeberg, J; Dusart, P; Edfors, F; Oksvold, P; von Feilitzen, K; Zwahlen, M; Arif, M; Altay, O; Li, X; Ozcan, M; Mardinoglu, A; Fagerberg, L; Mulder, J; Luo, Y; Ponten, F; Uhlén, M; Lindskog, C (July 2021). "A single-cell type transcriptomics map of human tissues". Science Advances. 7 (31). Bibcode:2021SciA....7.2169K. doi:10.1126/sciadv.abh2169. PMC 8318366 . PMID 34321199.

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