The DOI matches its Crossref record; 75 of the 75 references it cites were found in a registry or an index.
A complete mass-spectrometric map of the yeast proteome applied to quantitative trait analysis
Open accessAbstract
Experience from different fields of life sciences suggests that accessible, complete reference maps of the components of the system under study are highly beneficial research tools. Examples of such maps include libraries of the spectroscopic properties of molecules, or databases of drug structures in analytical or forensic chemistry. Such maps, and methods to navigate them, constitute reliable assays to probe any sample for the presence and amount of molecules contained in the map. So far, attempts to generate such maps for any proteome have failed to reach complete proteome coverage. Here we use a strategy based on high-throughput peptide synthesis and mass spectrometry to generate an almost complete reference map (97% of the genome-predicted proteins) of the Saccharomyces cerevisiae proteome. We generated two versions of this mass-spectrometric map, one supporting discovery-driven (shotgun) and the other supporting hypothesis-driven (targeted) proteomic measurements. Together, the two versions of the map constitute a complete set of proteomic assays to support most studies performed with contemporary proteomic technologies. To show the utility of the maps, we applied them to a protein quantitative trait locus (QTL) analysis, which requires precise measurement of the same set of peptides over a large number of samples. Protein measurements over 78 S. cerevisiae strains revealed a complex relationship between independent genetic loci, influencing the levels of related proteins. Our results suggest that selective pressure favours the acquisition of sets of polymorphisms that adapt protein levels but also maintain the stoichiometry of functionally related pathway members.
Overview
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
Verification
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?
In the citing paper
“Studies in model organisms have shown that variation in mRNA and protein expression levels are often uncorrelated (5-8).”
From Impact of regulatory variation from RNA to protein (2015) · cites this paper as [7]
In the citing paper
“The advance in quantitative proteomics allows a genome-wide map of pQTL model organisms (Foss et al., 2007; Picotti et al., 2013).”
From Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases (2016) · cites this paper as Picotti et al., 2013
In the citing paper
“Picotti et al. used a nearly complete map of yeast proteome and genetic variation data to identify strong genetic effects of protein abundance, and to demonstrate epistatic interactions affecting protein levels (Picotti et al., 2013).”
From Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases (2016) · cites this paper as Picotti et al., 2013
In the citing paper
“Using precise MS measurement of peptides over a large number of samples, recent pQTL analyses revealed complex genetic influence on the levels of proteins in yeast (Picotti et al., 2013) and mouse (Holdt et al., 2013).”
From Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases (2016) · cites this paper as Picotti et al., 2013
In the citing paper
“Human biology is tightly linked to proteins, and mass spectrometry-based proteomics has established a strong linkage between phenotype and protein-level biology (1, 2).”
From The Blood Proteoform Atlas: A reference map of proteoforms in human hematopoietic cells (2022) · cites this paper as [1]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The sequence of the human genome
Venter, J. C., Adams, M. D., Myers, E. W., Li, P. W., Mural, R. J., Sutton, G. G., Smith, H. O., Yandell, M., Evans, C. A., Holt, R. A., et al. (2001) · Science · doi:10.1126/science.1058040 · Cited by 13,909
Mass spectrometry-based proteomics
Aebersold, R., & Mann, M. (2003) · Nature · doi:10.1038/nature01511 · Cited by 6,955
Self-citationEng, J. K., McCormack, A. L., & Yates, J. R. (1994) · Journal of the American Society for Mass Spectrometry · doi:10.1016/1044-0305(94)80016-2 · Cited by 6,484
Whole-Genome Random Sequencing and Assembly of Haemophilus influenzae Rd
Fleischmann, R. D., Adams, M. D., White, O. R., Clayton, R. A., Kirkness, E. F., Kerlavage, A. R., Bult, C. J., Tomb, J.-F., Dougherty, B. A., Merrick, J. M., et al. (1995) · Science · doi:10.1126/science.7542800 · Cited by 5,731
Keller, A., Nesvizhskii, A., Kolker, E., & Aebersold, R. (2002) · Analytical Chemistry · doi:10.1021/ac025747h · Cited by 4,970
Self-citationQuantitative analysis of complex protein mixtures using isotope-coded affinity tags
Gygi, S. P., Rist, B., Gerber, S. A., Turecek, F., Gelb, M. H., & Aebersold, R. (1999) · Nature Biotechnology · doi:10.1038/13690 · Cited by 4,683
Self-citationBioGRID: a general repository for interaction datasets
Stark, C. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkj109 · Cited by 3,960
Global analysis of protein expression in yeast
Ghaemmaghami, S., Huh, W.-K., Bower, K., Howson, R. W., Belle, A., Dephoure, N., O'Shea, E. K., & Weissman, J. S. (2003) · Nature · doi:10.1038/nature02046 · Cited by 3,750
Gillet, L. C., Navarro, P., Tate, S., Röst, H., Selevsek, N., Reiter, L., Bonner, R., & Aebersold, R. (2012) · Molecular & Cellular Proteomics · doi:10.1074/mcp.o111.016717 · Cited by 2,877
Self-citationTANDEM: matching proteins with tandem mass spectra
Craig, R., & Beavis, R. C. (2004) · Bioinformatics · doi:10.1093/bioinformatics/bth092 · Cited by 2,546
Improved scoring of functional groups from gene expression data by decorrelating GO graph structure
Alexa, A., Rahnenführer, J., & Lengauer, T. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl140 · Cited by 2,194
Personal genomes: The case of the missing heritability
Maher, B. (2008) · Nature · doi:10.1038/456018a · Cited by 1,737
The Sequence of the Human Genome
Venter, J. C., Smith, H. O., & Adams, M. D. (2015) · Clinical Chemistry · doi:10.1373/clinchem.2014.237016 · Cited by 1,665
The mystery of missing heritability: Genetic interactions create phantom heritability
Zuk, O., Hechter, E., Sunyaev, S. R., & Lander, E. S. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1119675109 · Cited by 1,542
Open Mass Spectrometry Search Algorithm
Geer, L. Y., Markey, S. P., Kowalak, J. A., Wagner, L., Xu, M. Q., Maynard, D., Yang, X., Shi, W., & Bryant, S. H. (2004) · Journal of Proteome Research · doi:10.1021/pr0499491 · Cited by 1,420
Selected reaction monitoring for quantitative proteomics: a tutorial
Lange, V., Picotti, P., Domon, B., & Aebersold, R. H. (2008) · Molecular Systems Biology · doi:10.1038/msb.2008.61 · Cited by 1,396
Self-citationGenetic Dissection of Transcriptional Regulation in Budding Yeast
Brem, R. B., Yvert, G., Clinton, R., & Kruglyak, L. (2002) · Science · doi:10.1126/science.1069516 · Cited by 1,392
Quantitative mass spectrometric multiple reaction monitoring assays for major plasma proteins
Anderson, L., & Hunter, C. L. (2006) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m500331-mcp200 · Cited by 1,230
Bjellqvist, B., Hughes, G. J., Pasquali, C., Paquet, N., Ravier, F., Sanchez, J., Frutiger, S., & Hochstrasser, D. F. (1993) · Electrophoresis · doi:10.1002/elps.11501401163 · Cited by 1,017
Desiere, F. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkj040 · Cited by 910
Comprehensive mass-spectrometry-based proteome quantification of haploid versus diploid yeast
de Godoy, L. M. F., Olsen, J. V., Cox, J., Nielsen, M. L., Hubner, N. C., Fröhlich, F., Walther, T. C., & Mann, M. (2008) · Nature · doi:10.1038/nature07341 · Cited by 873
A common open representation of mass spectrometry data and its application to proteomics research
Pedrioli, P. G. A., Eng, J. K., Hubley, R. M., Vogelzang, M., Deutsch, E. W., Raught, B., Pratt, B. S., Nilsson, E. J., Angeletti, R. H., Apweiler, R., et al. (2004) · Nature Biotechnology · doi:10.1038/nbt1031 · Cited by 782
Self-citationFull dynamic range proteome analysis of S. cerevisiae by targeted proteomics
Picotti, P., Bodenmiller, B., Mueller, L. N., Domon, B., & Aebersold, R. (2009) · Cell · doi:10.1016/j.cell.2009.05.051 · Cited by 744
Self-citationA guided tour of the Trans‐Proteomic Pipeline
Deutsch, E. W., Mendoza, L., Shteynberg, D. D., Farrah, T., Lam, H., Tasman, N., Sun, Z., Nilsson, E. J., Pratt, B. S., Prazen, B. J., et al. (2010) · PROTEOMICS · doi:10.1002/pmic.200900375 · Cited by 744
Self-citationFrank, R. (2002) · Journal of Immunological Methods · doi:10.1016/s0022-1759(02)00137-0 · Cited by 742
Computational prediction of proteotypic peptides for quantitative proteomics
Mallick, P., Schirle, M., Chen, S. S., Flory, M. R., Lee, H., Martin, D. B., Ranish, J. A., Raught, B., Schmitt, R., Werner, T., et al. (2006) · Nature Biotechnology · doi:10.1038/nbt1275 · Cited by 714
Self-citationA Genecentric Human Protein Atlas for Expression Profiles Based on Antibodies
Berglund, L., Björling, E., Oksvold, P., Fagerberg, L., Asplund, A., Szigyarto, C. A., Persson, A. B., Ottosson, J. E. A., Wernérus, H., Nilsson, P., et al. (2008) · Molecular & Cellular Proteomics · doi:10.1074/mcp.r800013-mcp200 · Cited by 671
Comparative analysis of proteome and transcriptome variation in mouse
Ghazalpour, A., Bennett, B., Petyuk, V. A., Orozco, L., Hagopian, R., Mungrue, I. N., Farber, C. R., Sinsheimer, J., Kang, H. M., Furlotte, N., et al. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1001393 · Cited by 624
Options and considerations when selecting a quantitative proteomics strategy
Domon, B., & Aebersold, R. H. (2010) · Nature Biotechnology · doi:10.1038/nbt.1661 · Cited by 616
Self-citationUsing i RT , a normalized retention time for more targeted measurement of peptides
Escher, C., Reiter, L., MacLean, B., Ossola, R., Herzog, F., Chilton, J. M., MacCoss, M. J., & Rinner, O. (2012) · PROTEOMICS · doi:10.1002/pmic.201100463 · Cited by 597
Self-citationThe primary structure of the Saccharomyces cerevisiae gene for alcohol dehydrogenase.
Bennetzen, J. L., & Hall, B. D. (1982) · Journal of Biological Chemistry · doi:10.1016/s0021-9258(19)81067-0 · Cited by 557
Shteynberg, D. D., Deutsch, E. W., Lam, H., Eng, J. K., Sun, Z., Tasman, N., Mendoza, L., Moritz, R. L., Aebersold, R. H., & Nesvizhskii, A. I. (2011) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m111.007690 · Cited by 554
Self-citationPeptideAtlas: a resource for target selection for emerging targeted proteomics workflows
Deutsch, E. W., Lam, H., & Aebersold, R. H. (2008) · EMBO Reports · doi:10.1038/embor.2008.56 · Cited by 541
Self-citationmProphet: automated data processing and statistical validation for large-scale SRM experiments
Reiter, L., Rinner, O., Picotti, P., Hüttenhain, R., Beck, M., Brusniak, M.-Y., Hengartner, M. O., & Aebersold, R. (2011) · Nature Methods · doi:10.1038/nmeth.1584 · Cited by 532
Self-citationLam, H., Deutsch, E. W., Eddes, J. S., Eng, J. K., King, N., Stein, S. E., & Aebersold, R. (2007) · PROTEOMICS · doi:10.1002/pmic.200600625 · Cited by 517
Self-citationHigh-throughput generation of selected reaction-monitoring assays for proteins and proteomes
Picotti, P., Rinner, O., Stallmach, R., Dautel, F., Farrah, T., Domon, B., Wenschuh, H., & Aebersold, R. H. (2009) · Nature Methods · doi:10.1038/nmeth.1408 · Cited by 452
Self-citationScoring proteomes with proteotypic peptide probes
Küster, B., Schirle, M., Mallick, P., & Aebersold, R. H. (2005) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm1683 · Cited by 366
Self-citationHigh Sensitivity Detection of Plasma Proteins by Multiple Reaction Monitoring of N-Glycosites
Stahl-Zeng, J., Lange, V., Ossola, R., Eckhardt, K., Krek, W., Aebersold, R. H., & Domon, B. (2007) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m700132-mcp200 · Cited by 361
Self-citationGenetic basis of proteome variation in yeast
Foss, E. J., Radulovic, D., Shaffer, S. A., Ruderfer, D. M., Bedalov, A., Goodlett, D. R., & Kruglyak, L. (2007) · Nature Genetics · doi:10.1038/ng.2007.22 · Cited by 358
Bodenmiller, B., Wanka, S., Kraft, C., Urban, J., Campbell, D. S., Pedrioli, P. G. A., Gerrits, B., Picotti, P., Lam, H., Olga Vitek, A., et al. (2010) · Science Signaling · doi:10.1126/scisignal.2001182 · Cited by 306
Self-citationUsing Annotated Peptide Mass Spectrum Libraries for Protein Identification
Craig, R., Cortens, J. C., Fenyö, D., & Beavis, R. (2006) · Journal of Proteome Research · doi:10.1021/pr0602085 · Cited by 301
Krokhin, O. V., Craig, R., Spicer, V., Ens, W., Standing, K. G., Beavis, R. C., & Wilkins, J. A. (2004) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m400031-mcp200 · Cited by 284
Building consensus spectral libraries for peptide identification in proteomics
Lam, H., Deutsch, E. W., Eddes, J. S., Eng, J. K., Stein, S. E., & Aebersold, R. H. (2008) · Nature Methods · doi:10.1038/nmeth.1254 · Cited by 267
Self-citationReproducible Quantification of Cancer-Associated Proteins in Body Fluids Using Targeted Proteomics
Hüttenhain, R., Soste, M., Selevsek, N., Röst, H. L., Sethi, A., Carapito, C., Farrah, T., Deutsch, E. W., Kusebauch, U., Moritz, R. L., et al. (2012) · Science Translational Medicine · doi:10.1126/scitranslmed.3003989 · Cited by 249
Self-citationAnalysis of Peptide MS/MS Spectra from Large-Scale Proteomics Experiments Using Spectrum Libraries
Frewen, B. E., Merrihew, G. E., Wu, C. C., Noble, W. S., & MacCoss, M. J. (2006) · Analytical Chemistry · doi:10.1021/ac060279n · Cited by 249
Taussig, M., Stoevesandt, O., Borrebaeck, C. A. K., Bradbury, A. M., Cahill, D. J., Cambillau, C., de Daruvar, A., Dübel, S., Eichler, J., Frank, R., et al. (2006) · Nature Methods · doi:10.1038/nmeth0107-13 · Cited by 236
Krokhin, O. V. (2006) · Analytical Chemistry · doi:10.1021/ac060777w · Cited by 231
Efficient Fractionation and Improved Protein Identification by Peptide OFFGEL Electrophoresis
Hörth, P., Miller, C. A., Preckel, T., & Wenz, C. (2006) · Molecular & Cellular Proteomics · doi:10.1074/mcp.t600037-mcp200 · Cited by 224
A database of mass spectrometric assays for the yeast proteome
Picotti, P., Lam, H., Campbell, D. S., Deutsch, E. W., Mirzaei, H., Ranish, J. A., Domon, B., & Aebersold, R. H. (2008) · Nature Methods · doi:10.1038/nmeth1108-913 · Cited by 212
Self-citationMacLean, B., Eng, J. K., Beavis, R. C., & McIntosh, M. W. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl379 · Cited by 210
Lange, V., Malmström, J. A., Didion, J. P., King, N. L., Johansson, B. P., Schäfer, J., Rameseder, J., Wong, C., Deutsch, E. W., Brusniak, M., et al. (2008) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m800032-mcp200 · Cited by 204
Self-citationThe Implications of Proteolytic Background for Shotgun Proteomics
Picotti, P., Aebersold, R. H., & Domon, B. (2007) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m700029-mcp200 · Cited by 198
Self-citationGenerating and navigating proteome maps using mass spectrometry
Ahrens, C. H., Brunner, E., Qeli, E., Basler, K., & Aebersold, R. H. (2010) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm2973 · Cited by 171
Self-citationEvidence for widespread adaptive evolution of gene expression in budding yeast
Fraser, H. B., Moses, A. M., & Schadt, E. E. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0912245107 · Cited by 154
Young, E. T., & Pilgrim, D. B. (1985) · Molecular and Cellular Biology · doi:10.1128/mcb.5.11.3024-3034.1985 · Cited by 146
Schmidt, A., Gehlenborg, N., Bodenmiller, B., Mueller, L. N., Campbell, D., Mueller, M., Aebersold, R. H., & Domon, B. (2008) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m700498-mcp200 · Cited by 140
Self-citationDeutsch, E. W. (2009) · Methods in molecular biology · doi:10.1007/978-1-60761-444-9_19 · Cited by 139
Self-citationYoung, E. T., & Pilgrim, D. B. (1985) · Molecular and Cellular Biology · doi:10.1128/mcb.5.11.3024 · Cited by 116
Heller, M., Michel, P., Morier, P., Crettaz, D., Wenz, C., Tissot, J., Reymond, F., & Rossier, J. S. (2005) · Electrophoresis · doi:10.1002/elps.200410106 · Cited by 113
Genetic Variation Shapes Protein Networks Mainly through Non-transcriptional Mechanisms
Foss, E. J., Radulovic, D., Shaffer, S. A., Goodlett, D. R., Kruglyak, L., & Bedalov, A. (2011) · PLoS Biology · doi:10.1371/journal.pbio.1001144 · Cited by 108
Bootstrapping the Interactome: Unsupervised Identification of Protein Complexes in Yeast
Friedel, C. C., Krumsiek, J., & Zimmer, R. (2009) · Journal of Computational Biology · doi:10.1089/cmb.2009.0023 · Cited by 108
Absolute quantification of microbial proteomes at different states by directed mass spectrometry
Schmidt, A., Beck, M., Malmström, J. A., Lam, H., Claassen, M., Campbell, D. S., & Aebersold, R. H. (2011) · Molecular Systems Biology · doi:10.1038/msb.2011.37 · Cited by 103
Self-citationA Computational Tool to Detect and Avoid Redundancy in Selected Reaction Monitoring
Röst, H. L., Malmström, L., & Aebersold, R. H. (2012) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m111.013045 · Cited by 99
Self-citationde Smidt, O., du Preez, J. C., & Albertyn, J. (2011) · FEMS Yeast Research · doi:10.1111/j.1567-1364.2011.00760.x · Cited by 99
Analysis of the Saccharomyces cerevisiae proteome with PeptideAtlas
King, N. L., Deutsch, E. W., Ranish, J. A., Nesvizhskii, A. I., Eddes, J. S., Mallick, P., Eng, J. K., Desiere, F., Flory, M. R., Martin, D. B., et al. (2006) · Genome biology · doi:10.1186/gb-2006-7-11-r106 · Cited by 65
Self-citationColón‐González, M., Hernández, F., López, K. D., Quezada, H., González, J., López, G., Aranda, C., & González, A. (2011) · PLoS ONE · doi:10.1371/journal.pone.0016099 · Cited by 64
Data-driven assessment of eQTL mapping methods
Michaelson, J. J., Alberts, R., Schughart, K., & Beyer, A. (2010) · BMC Genomics · doi:10.1186/1471-2164-11-502 · Cited by 50
Self-citationSoftware Pipeline and Data Analysis for MS/MS Proteomics: The Trans-Proteomic Pipeline
Keller, A., & Shteynberg, D. D. (2010) · Methods in molecular biology · doi:10.1007/978-1-60761-977-2_12 · Cited by 46
Unique Ion Signature Mass Spectrometry, a Deterministic Method to Assign Peptide Identity
Sherman, J., McKay, M. J., Ashman, K., & Molloy, M. P. (2009) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m800512-mcp200 · Cited by 44
A pilot project to generate affinity reagents to human proteins
Uhlén, M., Gräslund, S., & Sundström, M. (2008) · Nature Methods · doi:10.1038/nmeth1008-854 · Cited by 32
Using the Human Plasma PeptideAtlas to Study Human Plasma Proteins
Farrah, T., Deutsch, E. W., & Aebersold, R. H. (2011) · Methods in molecular biology · doi:10.1007/978-1-61779-068-3_23 · Cited by 29
Self-citationSpectral Library Searching for Peptide Identification via Tandem MS
Lam, H., & Aebersold, R. H. (2009) · Methods in molecular biology · doi:10.1007/978-1-60761-444-9_7 · Cited by 20
Self-citationOpen Mass Spectrometry Search AlgorithmPreprint
Geer, L. Y., Markey, S. P., Kowalak, J. A., et al. (2004) · arXiv (Cornell University) · doi:10.48550/arxiv.q-bio/0406002 · Cited by 15
Teamwork: Improved eQTL Mapping Using Combinations of Machine Learning Methods
Ackermann, M., Clément‐Ziza, M., Michaelson, J. J., & Beyer, A. (2012) · PLoS ONE · doi:10.1371/journal.pone.0040916 · Cited by 13
Self-citationInterfaces to PeptideAtlas: a case study of standard data access systems
Killcoyne, S., Handcock, J., Robinson, T., Deutsch, E. W., & Boyle, J. (2011) · Briefings in Bioinformatics · doi:10.1093/bib/bbr067 · Cited by 1
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
On the Dependency of Cellular Protein Levels on mRNA Abundance
Liu, Y., Beyer, A., & Aebersold, R. (2016) · Cell · doi:10.1016/j.cell.2016.03.014 · Cited by 3,221
Self-citationMass-spectrometric exploration of proteome structure and function
Aebersold, R., & Mann, M. (2016) · Nature · doi:10.1038/nature19949 · Cited by 2,334
Self-citationA draft map of the human proteome
Kim, M.-S., Pinto, S. M., Getnet, D., Nirujogi, R. S., Manda, S. S., Chaerkady, R., Madugundu, A. K., Kelkar, D. S., Isserlin, R., Jain, S., et al. (2014) · Nature · doi:10.1038/nature13302 · Cited by 2,198
Self-citationThe proteostasis network and its decline in ageing
Hipp, M. S., Kasturi, P., & Hartl, F. U. (2019) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-019-0101-y · Cited by 1,642
The role of regulatory variation in complex traits and disease
Albert, F. W., & Kruglyak, L. (2015) · Nature Reviews Genetics · doi:10.1038/nrg3891 · Cited by 1,047
Metadata
- Authors
- Picotti, P., Clément-Ziza, M., Lam, H., Campbell, D. S., Schmidt, A., Deutsch, E. W., Röst, H., Sun, Z., Rinner, O., Reiter, L., Shen, Q., Michaelson, J. J., Frei, A., Alberti, S., Kusebauch, U., Wollscheid, B., Moritz, R. L., Beyer, A., & Aebersold, R.
- Affiliations
- ETH Zurich (CH)
- Hong Kong University of Science and Technology (HK)
- Institute for Systems Biology (US)
- University of Basel (CH)
- Chinese Academy of Sciences (CN)
- Biotechnologisches Zentrum (DE)
- Max Planck Institute of Molecular Cell Biology and Genetics (DE)
- University of Zurich (CH)
- Corresponding author
- Picotti, Paola
- Beyer, Andreas
- Aebersold, Ruedi
- ORCID
- Venue
- Nature
- Published
- 2013-01-20
- Volume
- 494
- Issue
- 7436
- Pages
- 266-270
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC3951219
- OpenAlex
- W2065096062
- Cited by
- 318
- References
- 73
- Citations by year
- 2026: 2 · 2025: 10 · 2024: 7 · 2023: 10 · 2022: 18 · 2021: 14 · 2020: 10 · 2019: 30 · 2018: 24 · 2017: 44 · 2016: 31 · 2015: 44 · 2014: 40 · 2013: 31
- FWCI
- 21.82
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Max Planck Institute for Plasma Physics (submittedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Rare & Special e-Zone (The Hong Kong University of Science and Technology) (submittedVersion)
- Funders
- Université du Luxembourg
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (133670, 107679)
- National Institutes of Health (n01hv28179-12-0-0)
- National Institute of Standards and Technology
- National Heart, Lung, and Blood Institute (N01 HV028179, N01-HV-28179)
- National Human Genome Research Institute (RC2HG005805)
- National Institute of General Medical Sciences (P50GM076547)
- Topics
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Physical Sciences › Chemistry › Spectroscopy › Mass Spectrometry Techniques and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Fungal and yeast genetics research
- Keywords
- proteome reference map, protein abundance, shotgun proteomics, targeted proteomics, genetic polymorphism, protein stoichiometry, selection pressure, yeast strain
- MeSH terms
- Polymorphism, Genetic, Reference Values, Saccharomyces cerevisiae, Selection, Genetic, Mass Spectrometry, Peptide Library, Proteome, Saccharomyces cerevisiae Proteins, Quantitative Trait Loci, Proteomics
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
