325:
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.
329:
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.
353:
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.
333:
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.
399:(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
27:
492:
759:
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).
378:
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.
758:
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;
324:
The Brain 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
291:
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
714:
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).
664:
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,
406:
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
377:
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
332:
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
348:
The Blood
Protein 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
328:
The Single Cell Type 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
336:
The
Pathology 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
352:
The
Subcellular 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
356:
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
808:
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;
562:
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;
344:
The Immune Cell 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
852:
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;
606:
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).
381:
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
372:
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.
312:
The Tissue 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
809:
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".
415:
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.
423:
on protocols.io. 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).
902:
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).
407:
fragments was carried out for a chromosome-wide protein profiling of chromosome 21. Other projects were also carried out to establish processes for parallel and automated affinity purification of mono-specific antibodies and their validation.
340:
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
288:. 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.
1206:
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".
1425:
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).
349:
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.
952:
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).
993:
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".
1483:
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).
1179:
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".
363:
The Interaction section presents data on interaction networks based on protein-protein interactions from the IntAct database and metabolic pathways from the Metabolic Atlas.
853:
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).
357:
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.
284:. 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
1244:"High MCM3 expression is an independent biomarker of poor prognosis and correlates with reduced RBM3 expression in a prospective cohort of malignant melanoma"
519:, Fagerberg L, Hallström BM, Lindskog C, Oksvold P, Mardinoglu A, et al. (January 2015). "Proteomics. Tissue-based map of the human proteome".
1368:
Uhlen, M; Bandrowski, A; Carr, S; Edwards, A; Ellenberg, J; Lundberg, E; Rimm, DL; Rodriguez, H; Hiltke, T; Snyder, M; Yamamoto, T (October 2016).
392:
297:
296:
as a European core resource due to its fundamental importance for a wider life science community. The HPA consortium is funded by the
75:
1079:"High RBM3 expression in prostate cancer independently predicts a reduced risk of biochemical recurrence and disease progression"
1293:
Schwenk JM, Igel U, Neiman M, Langen H, Becker C, Bjartell A, Ponten F, Wiklund F, Grönberg H, Nilsson P, Uhlen M (Nov 2010).
396:
277:
46:
portal is a publicly available database with millions of high-resolution images showing the spatial distribution of
1538:
760:
563:
Hökfelt, T; Uhlén, M; Mulder, J (2020). "An atlas of the protein-coding genes in the human, pig, and mouse brain".
1548:
478:
321:
stained normal tissues are available together with knowledge-based annotation of protein expression levels.
50:
in normal human tissues and different cancer types, as well the sub cellular localisation in single cells.
1128:
Larsson A, Fridberg M, Gaber A, Nodin B, Levéen P, Jönsson G, Uhlén M, Birgisson H, Jirström K (2012).
419:
Researchers involved with Human Protein Atlas projects, are sharing protocols and method details in an
954:"Affinity proteomics for systematic protein profiling of chromosome 21 gene products in human tissues"
1439:
620:
318:
314:
1543:
1295:"Toward next generation plasma profiling via heat-induced epitope retrieval and array-based assays"
360:
The Structure section contains information about the three-dimensional structure of human proteins.
197:
855:"The MIntAct project--IntAct as a common curation platform for 11 molecular interaction databases"
1407:
1018:
834:
790:
740:
696:
588:
544:
345:
classification based on specificity, distribution and expression cluster across all immune cells.
123:
79:
248:(HPA) is a Swedish-based program started in 2003 with the aim to map all the human proteins in
1514:
1465:
1399:
1326:
1275:
1224:
1188:
1161:
1130:"Validation of podocalyxin-like protein as a biomarker of poor prognosis in colorectal cancer"
1110:
1059:
1010:
975:
934:
884:
826:
782:
732:
688:
646:
580:
536:
391:
The Human Protein Atlas program was started in 2003 and funded by the non-profit organization
269:
115:
1504:
1496:
1455:
1447:
1389:
1381:
1316:
1306:
1265:
1255:
1216:
1151:
1141:
1100:
1090:
1049:
1002:
965:
924:
916:
874:
866:
818:
772:
724:
678:
636:
628:
572:
528:
516:
473:
400:
253:
107:
95:
1036:
Uhlén M, Björling E, Agaton C, Szigyarto CA, Amini B, Andersen E, et al. (Dec 2005).
281:
257:
182:
70:
1443:
1394:
1369:
624:
26:
1509:
1484:
1460:
1427:
1321:
1294:
1270:
1243:
1156:
1129:
1105:
1078:
929:
904:
879:
854:
641:
608:
249:
1344:
715:"A genome-wide transcriptomic analysis of protein-coding genes in human blood cells".
420:
1532:
794:
744:
700:
592:
1411:
1022:
838:
98:, et al. (January 2015). "Proteomics. Tissue-based map of the human proteome".
1500:
1038:"A human protein atlas for normal and cancer tissues based on antibody proteomics"
548:
500:
127:
1451:
1054:
1037:
970:
953:
920:
777:
273:
83:
1485:"Enhanced Validation of Antibodies Enables the Discovery of Missing Proteins"
1146:
161:
1311:
822:
728:
683:
666:
576:
532:
111:
1518:
1469:
1403:
1330:
1279:
1260:
1228:
1192:
1165:
1114:
1095:
1063:
1014:
979:
938:
888:
830:
786:
736:
692:
650:
632:
584:
540:
491:
461:
432:
The Human Protein Atlas program has participated in 9 EU research projects
119:
870:
285:
265:
55:
1385:
1242:
Nodin B, Fridberg M, Jonsson L, Bergman J, Uhlén M, Jirström K (2012).
1006:
47:
1220:
1077:
Jonsson L, Gaber A, Ulmert D, Uhlén M, Bjartell A, Jirström K (2011).
433:
293:
261:
496:
437:
145:
1428:"Enhanced validation of antibodies for research applications"
449:
445:
453:
609:"A single-cell type transcriptomics map of human tissues"
292:
biology and disease and was selected by the organization
441:
1345:"Human Protein Atlas - research group on protocols.io"
457:
667:"A pathology atlas of the human cancer transcriptome"
308:
The Human Protein Atlas consists of twelve sections:
501:
Creative Commons Attribution-ShareAlike 3.0 Unported
337:
each human protein gene and cancer patient survival.
232:
224:
216:
206:
196:
191:
181:
176:
156:
140:
135:
90:
69:
64:
54:
38:
33:
238:Yes – both individual protein entries and searches
665:C; Mardinoglu, A; Ponten, F (18 August 2017).
8:
19:
395:(KAW). The main site of the project is the
18:
1508:
1459:
1393:
1370:"A proposal for validation of antibodies"
1320:
1310:
1269:
1259:
1155:
1145:
1104:
1094:
1053:
969:
928:
878:
776:
682:
640:
187:Advanced search, bulk retrieval/download
508:
995:Biotechnology and Applied Biochemistry
7:
393:Knut and Alice Wallenberg Foundation
298:Knut and Alice Wallenberg Foundation
1299:Molecular & Cellular Proteomics
1042:Molecular & Cellular Proteomics
958:Molecular & Cellular Proteomics
14:
490:
403:is the director of the program.
25:
905:"An atlas of human metabolism"
1:
1501:10.1021/acs.jproteome.0c00486
499:, which is available under a
397:Royal Institute of Technology
260:using integration of various
1489:Journal of Proteome Research
1209:Journal of Proteome Research
865:(Database issue): D358-63.
317:. All underlying images of
1565:
1452:10.1038/s41467-018-06642-y
1055:10.1074/mcp.M500279-MCP200
971:10.1074/mcp.M300022-MCP200
16:Database of human proteins
921:10.1126/scisignal.aaz1482
778:10.1126/scisignal.aaz0274
24:
1147:10.1186/1471-2407-12-282
264:technologies, including
1312:10.1074/mcp.M110.001560
823:10.1126/science.aal3321
729:10.1126/science.aax9198
684:10.1126/science.aan2507
577:10.1126/science.aay5947
533:10.1126/science.1260419
497:The Human Protein Atlas
479:The Cancer Genome Atlas
112:10.1126/science.1260419
1261:10.1186/1746-1596-7-82
1096:10.1186/1746-1596-6-91
859:Nucleic Acids Research
633:10.1126/sciadv.abh2169
1432:Nature Communications
761:"The human secretome"
495:Text was copied from
1248:Diagnostic Pathology
1083:Diagnostic Pathology
319:immunohistochemistry
315:immunohistochemistry
1444:2018NatCo...9.4130E
871:10.1093/nar/gkt1115
625:2021SciA....7.2169K
368:Additional features
246:Human Protein Atlas
44:Human Protein Atlas
21:
20:Human Protein Atlas
1386:10.1038/nmeth.3995
1181:Discovery Medicine
1007:10.1042/BA20030091
1539:Protein databases
1495:(12): 4766–4781.
1221:10.1021/pr200286c
909:Science Signaling
765:Science Signaling
527:(6220): 1260419.
421:open-access group
341:machine-learning.
270:mass spectrometry
242:
241:
106:(6220): 1260419.
1556:
1549:Online databases
1523:
1522:
1512:
1480:
1474:
1473:
1463:
1422:
1416:
1415:
1397:
1365:
1359:
1358:
1356:
1355:
1341:
1335:
1334:
1324:
1314:
1305:(11): 2497–507.
1290:
1284:
1283:
1273:
1263:
1239:
1233:
1232:
1203:
1197:
1196:
1176:
1170:
1169:
1159:
1149:
1125:
1119:
1118:
1108:
1098:
1074:
1068:
1067:
1057:
1033:
1027:
1026:
990:
984:
983:
973:
949:
943:
942:
932:
899:
893:
892:
882:
849:
843:
842:
805:
799:
798:
780:
755:
749:
748:
711:
705:
704:
686:
661:
655:
654:
644:
613:Science Advances
603:
597:
596:
559:
553:
552:
513:
494:
474:Expression Atlas
268:-based imaging,
172:
169:
167:
165:
163:
152:
149:
147:
131:
91:Primary citation
29:
22:
1564:
1563:
1559:
1558:
1557:
1555:
1554:
1553:
1529:
1528:
1527:
1526:
1482:
1481:
1477:
1424:
1423:
1419:
1367:
1366:
1362:
1353:
1351:
1343:
1342:
1338:
1292:
1291:
1287:
1241:
1240:
1236:
1215:(11): 4925–34.
1205:
1204:
1200:
1178:
1177:
1173:
1127:
1126:
1122:
1076:
1075:
1071:
1048:(12): 1920–32.
1035:
1034:
1030:
1001:(Pt 3): 231–9.
992:
991:
987:
951:
950:
946:
901:
900:
896:
851:
850:
846:
807:
806:
802:
757:
756:
752:
713:
712:
708:
663:
662:
658:
605:
604:
600:
561:
560:
556:
515:
514:
510:
487:
470:
430:
413:
389:
370:
306:
304:Twelve sections
282:systems biology
278:transcriptomics
234:
225:Curation policy
208:
160:
144:
94:
71:Research center
17:
12:
11:
5:
1562:
1560:
1552:
1551:
1546:
1541:
1531:
1530:
1525:
1524:
1475:
1417:
1374:Nature Methods
1360:
1336:
1285:
1234:
1198:
1187:(49): 565–78.
1171:
1120:
1069:
1028:
985:
944:
894:
844:
800:
750:
706:
656:
598:
554:
507:
506:
505:
504:
486:
483:
482:
481:
476:
469:
466:
429:
428:Collaborations
426:
412:
409:
388:
385:
384:
383:
379:
369:
366:
365:
364:
361:
358:
354:
350:
346:
342:
338:
334:
330:
326:
322:
305:
302:
240:
239:
236:
230:
229:
226:
222:
221:
218:
214:
213:
210:
204:
203:
200:
194:
193:
189:
188:
185:
179:
178:
174:
173:
158:
154:
153:
142:
138:
137:
133:
132:
92:
88:
87:
73:
67:
66:
62:
61:
58:
52:
51:
40:
36:
35:
31:
30:
15:
13:
10:
9:
6:
4:
3:
2:
1561:
1550:
1547:
1545:
1542:
1540:
1537:
1536:
1534:
1520:
1516:
1511:
1506:
1502:
1498:
1494:
1490:
1486:
1479:
1476:
1471:
1467:
1462:
1457:
1453:
1449:
1445:
1441:
1437:
1433:
1429:
1421:
1418:
1413:
1409:
1405:
1401:
1396:
1391:
1387:
1383:
1380:(10): 823–7.
1379:
1375:
1371:
1364:
1361:
1350:
1346:
1340:
1337:
1332:
1328:
1323:
1318:
1313:
1308:
1304:
1300:
1296:
1289:
1286:
1281:
1277:
1272:
1267:
1262:
1257:
1253:
1249:
1245:
1238:
1235:
1230:
1226:
1222:
1218:
1214:
1210:
1202:
1199:
1194:
1190:
1186:
1182:
1175:
1172:
1167:
1163:
1158:
1153:
1148:
1143:
1139:
1135:
1131:
1124:
1121:
1116:
1112:
1107:
1102:
1097:
1092:
1088:
1084:
1080:
1073:
1070:
1065:
1061:
1056:
1051:
1047:
1043:
1039:
1032:
1029:
1024:
1020:
1016:
1012:
1008:
1004:
1000:
996:
989:
986:
981:
977:
972:
967:
964:(6): 405–14.
963:
959:
955:
948:
945:
940:
936:
931:
926:
922:
918:
914:
910:
906:
898:
895:
890:
886:
881:
876:
872:
868:
864:
860:
856:
848:
845:
840:
836:
832:
828:
824:
820:
816:
812:
804:
801:
796:
792:
788:
784:
779:
774:
770:
766:
762:
754:
751:
746:
742:
738:
734:
730:
726:
722:
718:
710:
707:
702:
698:
694:
690:
685:
680:
676:
672:
668:
660:
657:
652:
648:
643:
638:
634:
630:
626:
622:
618:
614:
610:
602:
599:
594:
590:
586:
582:
578:
574:
570:
566:
558:
555:
550:
546:
542:
538:
534:
530:
526:
522:
518:
512:
509:
502:
498:
493:
489:
488:
484:
480:
477:
475:
472:
471:
467:
465:
463:
459:
455:
451:
447:
443:
439:
435:
427:
425:
422:
417:
410:
408:
404:
402:
401:Mathias Uhlén
398:
394:
386:
380:
376:
375:
374:
367:
362:
359:
355:
351:
347:
343:
339:
335:
331:
327:
323:
320:
316:
311:
310:
309:
303:
301:
299:
295:
289:
287:
283:
279:
275:
271:
267:
263:
259:
255:
251:
247:
237:
231:
227:
223:
219:
215:
211:
205:
201:
199:
195:
192:Miscellaneous
190:
186:
184:
180:
175:
171:
164:.proteinatlas
159:
155:
151:
148:.proteinatlas
143:
139:
134:
129:
125:
121:
117:
113:
109:
105:
101:
97:
93:
89:
85:
81:
77:
74:
72:
68:
63:
59:
57:
53:
49:
45:
41:
37:
32:
28:
23:
1492:
1488:
1478:
1435:
1431:
1420:
1377:
1373:
1363:
1352:. Retrieved
1349:protocols.io
1348:
1339:
1302:
1298:
1288:
1251:
1247:
1237:
1212:
1208:
1201:
1184:
1180:
1174:
1137:
1133:
1123:
1086:
1082:
1072:
1045:
1041:
1031:
998:
994:
988:
961:
957:
947:
912:
908:
897:
862:
858:
847:
814:
810:
803:
768:
764:
753:
720:
716:
709:
674:
670:
659:
616:
612:
601:
568:
564:
557:
524:
520:
511:
464:and PRIMES.
431:
418:
414:
405:
390:
371:
307:
290:
245:
243:
233:Bookmarkable
228:Yes – manual
207:Data release
157:Download URL
103:
99:
43:
1438:(1): 4130.
39:Description
1544:Proteomics
1533:Categories
1354:2019-12-12
1134:BMC Cancer
485:References
446:AFFINOMICS
274:proteomics
198:Versioning
84:SciLifeLab
795:208321549
745:209424418
701:206659235
593:212560645
454:EURATRANS
438:PROSPECTS
212:12 months
209:frequency
170:/download
56:Organisms
1519:33170010
1470:30297845
1412:34259132
1404:27595404
1395:10335836
1331:20682762
1280:22805320
1229:21888404
1193:20587347
1166:22769594
1115:21955582
1064:16127175
1023:43820440
1015:12875650
980:12796447
939:32209698
889:24234451
839:10744558
831:28495876
817:(6340).
787:31772123
737:31857451
723:(6472).
693:28818916
677:(6352).
651:34321199
585:32139519
571:(6482).
541:25613900
503:license.
468:See also
411:Research
286:proteome
266:antibody
235:entities
120:25613900
86:, Sweden
48:proteins
1510:7723238
1461:6175901
1440:Bibcode
1322:2984230
1271:3433373
1157:3492217
1140:: 282.
1106:3195697
930:7331181
915:(624).
880:3965093
811:Science
771:(609).
717:Science
671:Science
642:8318366
621:Bibcode
565:Science
521:Science
517:Uhlén M
450:CAGEKID
442:BIO_NMD
387:History
382:assays.
272:-based
254:tissues
217:Version
141:Website
100:Science
96:Uhlén M
65:Contact
34:Content
1517:
1507:
1468:
1458:
1410:
1402:
1392:
1329:
1319:
1278:
1268:
1254:: 82.
1227:
1191:
1164:
1154:
1113:
1103:
1089:: 91.
1062:
1021:
1013:
978:
937:
927:
887:
877:
837:
829:
793:
785:
743:
735:
699:
691:
649:
639:
619:(31).
591:
583:
549:802377
547:
539:
462:DIRECT
434:ENGAGE
294:ELIXIR
258:organs
168:/about
136:Access
128:802377
126:
118:
1408:S2CID
1019:S2CID
835:S2CID
791:S2CID
741:S2CID
697:S2CID
589:S2CID
545:S2CID
458:ITFoM
262:omics
250:cells
177:Tools
124:S2CID
60:Human
1515:PMID
1466:PMID
1400:PMID
1327:PMID
1276:PMID
1225:PMID
1189:PMID
1162:PMID
1111:PMID
1060:PMID
1011:PMID
976:PMID
935:PMID
885:PMID
827:PMID
783:PMID
733:PMID
689:PMID
647:PMID
581:PMID
537:PMID
280:and
256:and
244:The
166:.org
150:.org
116:PMID
42:The
1505:PMC
1497:doi
1456:PMC
1448:doi
1390:PMC
1382:doi
1317:PMC
1307:doi
1266:PMC
1256:doi
1217:doi
1152:PMC
1142:doi
1101:PMC
1091:doi
1050:doi
1003:doi
966:doi
925:PMC
917:doi
875:PMC
867:doi
819:doi
815:356
773:doi
725:doi
721:366
679:doi
675:357
637:PMC
629:doi
573:doi
569:367
529:doi
525:347
202:Yes
183:Web
162:www
146:www
108:doi
104:347
76:KTH
1535::
1513:.
1503:.
1493:19
1491:.
1487:.
1464:.
1454:.
1446:.
1434:.
1430:.
1406:.
1398:.
1388:.
1378:13
1376:.
1372:.
1347:.
1325:.
1315:.
1301:.
1297:.
1274:.
1264:.
1250:.
1246:.
1223:.
1213:10
1211:.
1183:.
1160:.
1150:.
1138:12
1136:.
1132:.
1109:.
1099:.
1085:.
1081:.
1058:.
1044:.
1040:.
1017:.
1009:.
999:38
997:.
974:.
960:.
956:.
933:.
923:.
913:13
911:.
907:.
883:.
873:.
863:42
861:.
857:.
833:.
825:.
813:.
789:.
781:.
769:12
767:.
763:.
739:.
731:.
719:.
695:.
687:.
673:.
669:.
645:.
635:.
627:.
615:.
611:.
587:.
579:.
567:.
543:.
535:.
523:.
460:,
456:,
452:,
448:,
444:,
440:,
436:,
300:.
276:,
252:,
220:23
122:.
114:.
102:.
82:,
80:UU
78:,
1521:.
1499::
1472:.
1450::
1442::
1436:9
1414:.
1384::
1357:.
1333:.
1309::
1303:9
1282:.
1258::
1252:7
1231:.
1219::
1195:.
1185:9
1168:.
1144::
1117:.
1093::
1087:6
1066:.
1052::
1046:4
1025:.
1005::
982:.
968::
962:2
941:.
919::
891:.
869::
841:.
821::
797:.
775::
747:.
727::
703:.
681::
653:.
631::
623::
617:7
595:.
575::
551:.
531::
130:.
110::
Text is available under the Creative Commons Attribution-ShareAlike License. Additional terms may apply.