Extensive Peptide Fractionation and y1 Ion-Based Interference Detection Method for Enabling Accurate Quantification by Isobaric Labeling and Mass Spectrometry
Open accessAbstract
Isobaric labeling quantification by mass spectrometry (MS) has emerged as a powerful technology for multiplexed large-scale protein profiling, but measurement accuracy in complex mixtures is confounded by the interference from coisolated ions, resulting in ratio compression. Here we report that the ratio compression can be essentially resolved by the combination of pre-MS peptide fractionation, MS2-based interference detection, and post-MS computational interference correction. To recapitulate the complexity of biological samples, we pooled tandem mass tag (TMT)-labeled Escherichia coli peptides at 1:3:10 ratios and added in ∼20-fold more rat peptides as background, followed by the analysis of two-dimensional liquid chromatography (LC)–MS/MS. Systematic investigation shows that quantitative interference was impacted by LC fractionation depth, MS isolation window, and peptide loading amount. Exhaustive fractionation (320 × 4 h) can nearly eliminate the interference and achieve results comparable to the MS3-based method. Importantly, the interference in MS2 scans can be estimated by the intensity of contaminated y 1 product ions, and we thus developed an algorithm to correct reporter ion ratios of tryptic peptides. Our data indicate that intermediate fractionation (40 × 2 h) and y 1 ion-based correction allow accurate and deep TMT profiling of more than 10 000 proteins, which represents a straightforward and affordable strategy in isobaric labeling proteomics.
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?
The acquisition of rich proteomic information is largely attributed to access to high quality AD brain tissue and the strength of the optimized MS-based proteomics platform.
“The acquisition of such rich proteomic information is largely attributed to the access to high quality AD brain tissue (Beach et al., 2015) and the strength of the optimized mass spectrometry-based proteomics platform, including multiplex TMT isobaric labeling (Niu et al., 2017), extensive long gradient LC/LC coupled with high resolution MS/MS analysis (Wang et al., 2015), a refined phosphopeptide”
From Deep Multilayer Brain Proteomics Identifies Molecular Networks in Alzheimer’s Disease Progression (2020) · cites this paper as Niu et al., 2017
Ratio compression during TMT quantification due to peptide co-elution can be addressed by MS3, extensive LC fractionation, MS optimization, and computational correction.
“Although ratio compression occurs during quantification because of peptide co-elution, the limitation can be addressed by the introduction of the MS3 method [23], extensive LC fractionation, MS optimization, and computational correction [24], to allow deep proteomic analysis [18, 25, 26].”
From Integrated analysis of ultra-deep proteomes in cortex, cerebrospinal fluid and serum reveals a mitochondrial signature in Alzheimer’s disease (2020) · cites this paper as [24]
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
Ross, P. L., Huang, Y. N., Marchese, J. N., Williamson, B., Parker, K., Hattan, S., Khainovski, N., Pillai, S., Dey, S., Daniels, S., et al. (2004) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m400129-mcp200 · Cited by 4,401 · see citing works
Elias, J. E., & Gygi, S. P. (2007) · Nature Methods · doi:10.1038/nmeth1019 · Cited by 3,925 · see citing works
Thompson, A., Schäfer, J., Kuhn, K., Kienle, S., Schwarz, J., Schmidt, G., Neumann, T., & Hamon, C. (2003) · Analytical Chemistry · doi:10.1021/ac0262560 · Cited by 2,386 · see citing works
Mass-spectrometric exploration of proteome structure and function
Aebersold, R., & Mann, M. (2016) · Nature · doi:10.1038/nature19949 · Cited by 2,334 · see citing works
Protein biomarker discovery and validation: the long and uncertain path to clinical utility
Rifai, N., Gillette, M. A., & Carr, S. A. (2006) · Nature Biotechnology · doi:10.1038/nbt1235 · Cited by 1,867 · see citing works
Proteogenomics connects somatic mutations to signalling in breast cancer
CPTAC, N., Mertins, P., Mani, D. R., Ruggles, K. V., Gillette, M. A., Clauser, K. R., Wang, P., Wang, X., Qiao, J. W., Cao, S., et al. (2016) · Nature · doi:10.1038/nature18003 · Cited by 1,676 · see citing works
Self-citationPeng, J., Elias, J. E., Thoreen, C. C., Licklider, L., & Gygi, S. P. (2002) · Journal of Proteome Research · doi:10.1021/pr025556v · Cited by 1,652 · see citing works
Self-citationMcAlister, G. C., Nusinow, D. P., Jedrychowski, M. P., Wühr, M., Huttlin, E. L., Erickson, B. K., Rad, R., Haas, W., & Gygi, S. P. (2014) · Analytical Chemistry · doi:10.1021/ac502040v · Cited by 1,263 · see citing works
Proteomics by Mass Spectrometry: Approaches, Advances, and Applications
Yates, J. R., Ruse, C. I., & Nakorchevsky, A. (2009) · Annual Review of Biomedical Engineering · doi:10.1146/annurev-bioeng-061008-124934 · Cited by 1,078 · see citing works
Integrated Proteogenomic Characterization of Human High-Grade Serous Ovarian Cancer
Zhang, H., Liu, T., Zhang, Z., Payne, S. H., Zhang, B., McDermott, J. E., Zhou, J.-Y., Petyuk, V. A., Chen, L., Ray, D., et al. (2016) · Cell · doi:10.1016/j.cell.2016.05.069 · Cited by 1,029 · see citing works
Self-citationMS3 eliminates ratio distortion in isobaric multiplexed quantitative proteomics
Ting, L., Rad, R., Gygi, S. P., & Haas, W. (2011) · Nature Methods · doi:10.1038/nmeth.1714 · Cited by 1,009 · see citing works
Next-generation proteomics: towards an integrative view of proteome dynamics
Altelaar, M. A. F., Muñoz, J., & Heck, A. J. R. (2012) · Nature Reviews Genetics · doi:10.1038/nrg3356 · Cited by 776 · see citing works
Isobaric Labeling-Based Relative Quantification in Shotgun Proteomics
Rauniyar, N., & Yates, J. R. (2014) · Journal of Proteome Research · doi:10.1021/pr500880b · Cited by 597 · see citing works
Addressing Accuracy and Precision Issues in iTRAQ Quantitation
Karp, N. A., Huber, W. K., Sadowski, P. G., Charles, P. D., Hester, S. V., & Lilley, K. S. (2010) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m900628-mcp200 · Cited by 497 · see citing works
iTRAQ Underestimation in Simple and Complex Mixtures: “The Good, the Bad and the Ugly”
Ow, S. Y., Salim, M., Noirel, J., Evans, C. A., Rehman, I., & Wright, P. C. (2009) · Journal of Proteome Research · doi:10.1021/pr900634c · Cited by 490 · see citing works
Defining the consequences of genetic variation on a proteome-wide scale
Chick, J. M., Munger, S. C., Simecek, P., Huttlin, E. L., Choi, K., Gatti, D. M., Raghupathy, N., Svenson, K. L., Churchill, G. A., & Gygi, S. P. (2016) · Nature · doi:10.1038/nature18270 · Cited by 361 · see citing works
Scheltema, R. A., Hauschild, J.-P., Lange, O., Hornburg, D., Denisov, E. V., Damoc, E., Kuehn, A., Makarov, A., & Mann, M. (2014) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m114.043489 · Cited by 321 · see citing works
Measuring and Managing Ratio Compression for Accurate iTRAQ/TMT Quantification
Savitski, M. M., Mathieson, T., Zinn, N., Sweetman, G. M. A., Doce, C., Becher, I., Pachl, F., Küster, B., & Bantscheff, M. (2013) · Journal of Proteome Research · doi:10.1021/pr400098r · Cited by 278 · see citing works
Gas-phase purification enables accurate, multiplexed proteome quantification with isobaric tagging
Wenger, C. D., Lee, M. V., Hebert, A. S., McAlister, G. C., Phanstiel, D. H., Westphall, M. S., & Coon, J. J. (2011) · Nature Methods · doi:10.1038/nmeth.1716 · Cited by 244 · see citing works
Robust and Sensitive iTRAQ Quantification on an LTQ Orbitrap Mass Spectrometer
Bantscheff, M., Böesche, M., Eberhard, D., Mathieson, T., Sweetman, G. M. A., & Küster, B. (2008) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m800029-mcp200 · Cited by 235 · see citing works
Efficacy of Retinoids in IKZF1-Mutated BCR-ABL1 Acute Lymphoblastic Leukemia
Churchman, M. L., Low, J. A., Qu, C., Paietta, E. M., Kasper, L. H., Chang, Y., Payne-Turner, D., Althoff, M. J., Song, G., Chen, S.-C., et al. (2015) · Cancer Cell · doi:10.1016/j.ccell.2015.07.016 · Cited by 203 · see citing works
Self-citationSystematical Optimization of Reverse-Phase Chromatography for Shotgun Proteomics
Xu, P., Duong, D. M., & Peng, J. (2009) · Journal of Proteome Research · doi:10.1021/pr900251d · Cited by 202 · see citing works
Self-citationJUMP: a tag-based database search tool for peptide identification with high sensitivity and accuracy
Wang, X., Li, Y., Wu, Z., Wang, H., Tan, H., & Peng, J. (2014) · Molecular & Cellular Proteomics · doi:10.1074/mcp.o114.039586 · Cited by 194 · see citing works
Self-citationAhrné, E., Glatter, T., Viganó, C., von Schubert, C., Nigg, E. A., & Schmidt, A. (2016) · Journal of Proteome Research · doi:10.1021/acs.jproteome.6b00066 · Cited by 165 · see citing works
Erickson, B. K., Jedrychowski, M. P., McAlister, G. C., Everley, R. A., Kunz, R. C., & Gygi, S. P. (2014) · Analytical Chemistry · doi:10.1021/ac503934f · Cited by 159 · see citing works
High-Resolution Enabled 12-Plex DiLeu Isobaric Tags for Quantitative Proteomics
Frost, D. C., Greer, T., & Li, L. (2014) · Analytical Chemistry · doi:10.1021/ac503276z · Cited by 149 · see citing works
Accurate Multiplexed Proteomics at the MS2 Level Using the Complement Reporter Ion Cluster
Wühr, M., Haas, W., McAlister, G. C., Peshkin, L., Rad, R., Kirschner, M. W., & Gygi, S. P. (2012) · Analytical Chemistry · doi:10.1021/ac301962s · Cited by 147 · see citing works
Ow, S. Y., Salim, M., Noirel, J., Evans, C. A., & Wright, P. C. (2011) · PROTEOMICS · doi:10.1002/pmic.201000752 · Cited by 132 · see citing works
Synaptic Protein Ubiquitination in Rat Brain Revealed by Antibody-based Ubiquitome Analysis
Na, C. H., Jones, D. R., Yang, Y., Wang, X., Xu, Y., & Peng, J. (2012) · Journal of Proteome Research · doi:10.1021/pr300536k · Cited by 128 · see citing works
Self-citationBai, B., Tan, H., Pagala, V., High, A. A., Ichhaporia, V. P., Hendershot, L. M., & Peng, J. (2016) · Methods in enzymology on CD-ROM/Methods in enzymology · doi:10.1016/bs.mie.2016.10.007 · Cited by 119 · see citing works
Self-citationSavitski, M. M., Sweetman, G. M. A., Askenazi, M., Marto, J. A., Lang, M., Zinn, N., & Bantscheff, M. (2011) · Analytical Chemistry · doi:10.1021/ac201760x · Cited by 108 · see citing works
Wang, H., Yang, Y., Li, Y., Bai, B., Wang, X., Tan, H., Liu, T., Beach, T. G., Peng, J., & Wu, Z. (2015) · Journal of Proteome Research · doi:10.1021/pr500882h · Cited by 96 · see citing works
Self-citationGenome-scale proteome quantification by DEEP SEQ mass spectrometry
Zhou, F., Lu, Y., Ficarro, S. B., Adelmant, G., Jiang, W., Luckey, C. J., & Marto, J. A. (2013) · Nature Communications · doi:10.1038/ncomms3171 · Cited by 92 · see citing works
Sandberg, A., Branca, R. M., Lehtiö, J., & Forshed, J. (2013) · Journal of Proteomics · doi:10.1016/j.jprot.2013.10.035 · Cited by 88 · see citing works
Li, Y., Wang, X., Cho, J.-H., Shaw, T. I., Wu, Z., Bai, B., Wang, H., Zhou, S., Beach, T. G., Wu, G., et al. (2016) · Journal of Proteome Research · doi:10.1021/acs.jproteome.6b00344 · Cited by 88 · see citing works
Self-citationQuantitative Protein Analysis by Mass Spectrometry
Pagala, V., High, A. A., Wang, X., Tan, H., Kodali, K., Mishra, A., Kavdia, K., Xu, Y., Wu, Z., & Peng, J. (2015) · Methods in molecular biology · doi:10.1007/978-1-4939-2425-7_17 · Cited by 66 · see citing works
Self-citationTan, H., Wu, Z., Wang, H., Bai, B., Li, Y., Wang, X., Zhai, B., Beach, T. G., & Peng, J. (2014) · PROTEOMICS · doi:10.1002/pmic.201400171 · Cited by 58 · see citing works
Self-citationMertz, J. L., Tan, H., Pagala, V., Bai, B., Chen, P., Li, Y., Cho, J., Shaw, T. I., Wang, X., & Peng, J. (2015) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m114.045898 · Cited by 40 · see citing works
Self-citationHanna, J. A., Garcia, M. R., Go, J. C., Finkelstein, D., Kodali, K., Pagala, V., Wang, X., Peng, J., & Hatley, M. E. (2016) · Cell Death and Disease · doi:10.1038/cddis.2016.159 · Cited by 36 · see citing works
Self-citationLiu, J. M., Sweredoski, M. J., & Hess, S. Y. (2016) · Analytical Chemistry · doi:10.1021/acs.analchem.6b01067 · Cited by 21 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- [10]Mertins P Mani DR Ruggles KV Gillette MA Clauser KR Wang P Wang X Qiao JW Cao S Petralia F Kawaler E Mundt F Krug K Tu Z Lei JT Gatza ML Wilkerson M Perou CM Yellapantula V Huang KL Lin C McLellan MD Yan P Davies SR Townsend RR Skates SJ Wang J Zhang B Kinsinger CR Mesri M Rodriguez H Ding L Paulovich AG Fenyo D Ellis MJ Carr SA Nci C Nature 2016 534 55 62 27251275 PMC5102256
Cited by
Sorted by citations
Deep Multilayer Brain Proteomics Identifies Molecular Networks in Alzheimer’s Disease Progression
Bai, B., Wang, X., Li, Y., Chen, P.-C., Yu, K., Dey, K. K., Yarbro, J. M., Han, X., Lutz, B. M., Rao, S., et al. (2020) · Neuron · doi:10.1016/j.neuron.2019.12.015 · Cited by 632 · see citing works
“Exhaustive LC/LC-MS/MS improved quantitative accuracy and proteome coverage (Niu et al., 2017), quantifying 14,513 proteins (12,018 genes, false discovery rate (FDR) < 1%, Data S2B), and 34,173 phosphosites (46,612 phosphopeptides, FDR < 1%, Data S2C) (Figure 1B and Figures S3A-S3C).”
BackgroundMethodInfluentialSelf-citationProteomic landscape of Alzheimer’s Disease: novel insights into pathogenesis and biomarker discovery
Bai, B., Vanderwall, D., Li, Y., Wang, X., Poudel, S., Wang, H., Dey, K. K., Chen, P., Yang, K., & Peng, J. (2021) · Molecular Neurodegeneration · doi:10.1186/s13024-021-00474-z · Cited by 252 · see citing works
Self-citationDeng, Z., Lim, J., Wang, Q., Purtell, K., Wu, S., Palomo, G. M., Tan, H., Manfredi, G., Zhao, Y., Peng, J., et al. (2019) · Autophagy · doi:10.1080/15548627.2019.1644076 · Cited by 232 · see citing works
Self-citationWang, H., Dey, K. K., Chen, P.-C., Li, Y., Niu, M., Cho, J.-H., Wang, X., Bai, B., Jiao, Y., Chepyala, S. R., et al. (2020) · Molecular Neurodegeneration · doi:10.1186/s13024-020-00384-6 · Cited by 210 · see citing works
Self-citationLiu, C.-C., Zhao, J., Fu, Y., Inoue, Y., Ren, Y., Chen, Y., Doss, S. V., Shue, F., Jeevaratnam, S., Bastea, L., et al. (2022) · Nature Neuroscience · doi:10.1038/s41593-022-01127-0 · Cited by 168 · see citing works
Self-citationStewart, E., McEvoy, J., Wang, H., Chen, X., Honnell, V., Ocarz, M., Gordon, B., Dapper, J., Blankenship, K., Yang, Y., et al. (2018) · Cancer Cell · doi:10.1016/j.ccell.2018.07.012 · Cited by 153 · see citing works
Self-citationHigh-throughput proteomics and AI for cancer biomarker discovery
Xiao, Q., Zhang, F., Xu, L., Yue, L., Kon, O. L., Zhu, Y., & Guo, T. (2021) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2021.113844 · Cited by 150 · see citing works
Control of Early B Cell Development by the RNA N6-Methyladenosine Methylation
Zheng, Z., Zhang, L., Cui, X., Yu, X., Hsu, P. J., Lyu, R., Tan, H., Mandal, M., Zhang, M. H., Sun, H., et al. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.107819 · Cited by 137 · see citing works
Self-citationDeep undepleted human serum proteome profiling toward biomarker discovery for Alzheimer’s disease
Dey, K. K., Wang, H., Niu, M., Bai, B., Wang, X., Li, Y., Cho, J.-H., Tan, H., Mishra, A., High, A. A., et al. (2019) · Clinical Proteomics · doi:10.1186/s12014-019-9237-1 · Cited by 135 · see citing works
Self-citation27-Plex Tandem Mass Tag Mass Spectrometry for Profiling Brain Proteome in Alzheimer’s Disease
Wang, Z., Yu, K., Tan, H., Wu, Z., Cho, J.-H., Han, X., Sun, H., Beach, T. G., & Peng, J. (2020) · Analytical Chemistry · doi:10.1021/acs.analchem.0c00655 · Cited by 113 · see citing works
Self-citationBlocking an N-terminal acetylation–dependent protein interaction inhibits an E3 ligase
Scott, D. C., Hammill, J. T., Min, J., Rhee, D. Y., Connelly, M., Sviderskiy, V. O., Bhasin, D., Chen, Y., Ong, S. S., Chai, S. C., et al. (2017) · Nature Chemical Biology · doi:10.1038/nchembio.2386 · Cited by 108 · see citing works
Self-citationAdvances in mass spectrometry‐based glycomics
Dong, X., Huang, Y.-F., Cho, B. G., Zhong, J., Gautam, S., Peng, W.-J., Williamson, S. D., Banazadeh, A., Torres-Ulloa, K. Y., & Mechref, Y. (2018) · Electrophoresis · doi:10.1002/elps.201800273 · Cited by 80 · see citing works
Novel specialized cell state and spatial compartments within the germinal center
Kennedy, D. E., Okoreeh, M. K., Maienschein‐Cline, M., Ai, J., Veselits, M., McLean, K. C., Dhungana, Y., Wang, H., Peng, J., Chi, H., et al. (2020) · Nature Immunology · doi:10.1038/s41590-020-0660-2 · Cited by 95 · see citing works
Self-citationZeleke, T. Z., Pan, Q., Chiuzan, C. C., Onishi, M., Li, Y., Tan, H., Alvarez, M. J., Honan, E., Yang, M., Chia, P. L., et al. (2022) · Nature Cancer · doi:10.1038/s43018-022-00489-5 · Cited by 84 · see citing works
Self-citationYang, S. W., Li, L., Connelly, J. P., Porter, S. N., Kodali, K., Gan, H., Park, J. M., Tacer, K. F., Tillman, H., Peng, J., et al. (2020) · Molecular Cell · doi:10.1016/j.molcel.2019.12.022 · Cited by 79 · see citing works
Self-citationHunt, L. C., Graça, F. A., Pagala, V., Wang, Y., Li, Y., Yuan, Z., Fan, Y., Labelle, M., Peng, J., & Demontis, F. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.109971 · Cited by 69 · see citing works
Self-citationWang, H., Diaz, A. K., Shaw, T. I., Li, Y., Niu, M., Cho, J.-H., Paugh, B. S., Zhang, Y., Sifford, J. M., Bai, B., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-11661-4 · Cited by 67 · see citing works
Self-citationZhang, Z., Yu, K., You, Y., Jiang, P., Wu, Z., Deture, M. A., Dickson, D. W., Ikezu, S., Peng, J., & Ikezu, T. (2023) · Journal of Extracellular Vesicles · doi:10.1002/jev2.12358 · Cited by 67 · see citing works
Self-citationChen, P., Han, X., Shaw, T. I., Fu, Y., Sun, H., Niu, M., Wang, Z., Jiao, Y., Teubner, B. J. W., Eddins, D. M., et al. (2022) · Nature Aging · doi:10.1038/s43587-022-00290-0 · Cited by 60 · see citing works
Self-citationAcute depletion of CTCF rewires genome-wide chromatin accessibility
Xu, B., Wang, H., Wright, S., Hyle, J. W., Zhang, Y., Shao, Y., Niu, M., Fan, Y., Rosikiewicz, W., Djekidel, M. N., et al. (2021) · Genome biology · doi:10.1186/s13059-021-02466-0 · Cited by 57 · see citing works
Self-citationA Tutorial Review of Labeling Methods in Mass Spectrometry-Based Quantitative Proteomics
Wang, Z., Liu, P.-K., & Li, L. (2024) · ACS Measurement Science Au · doi:10.1021/acsmeasuresciau.4c00007 · Cited by 57 · see citing works
Mulligan, M. K., Abreo, T. J., Neuner, S. M., Parks, C., Watkins, C. E., Houseal, M. T., Shapaker, T. M., Hook, M., Tan, H., Wang, X., et al. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.00188 · Cited by 56 · see citing works
Self-citationConverging mechanism of UM171 and KBTBD4 neomorphic cancer mutations
Xie, X., Zhang, O., Yeo, M. J. R., Lee, C., Tao, R., Harry, S. A., Payne, N. C., Nam, E., Paul, L., Li, Y., et al. (2025) · Nature · doi:10.1038/s41586-024-08533-3 · Cited by 50 · see citing works
Self-citationTurnover atlas of proteome and phosphoproteome across mouse tissues and brain regions
Li, W., Dasgupta, A., Yang, K., Wang, S., Kumar, N. H., Chepyala, S. R., Yarbro, J. M., Hu, Z., Šalovská, B., Fornasiero, E. F., et al. (2025) · Cell · doi:10.1016/j.cell.2025.02.021 · Cited by 47 · see citing works
Self-citationBell, M. R., Lange, S., Sejdiu, B. I., Ibañez-Vega, J., Shi, H., Sun, X., Meng, X., Nguyen, P., Sutton, M. T., Wagner, J., et al. (2023) · Nature Biomedical Engineering · doi:10.1038/s41551-023-01143-w · Cited by 45 · see citing works
Self-citationMultiscale proteomic modeling reveals protein networks driving Alzheimer’s disease pathogenesis
Wang, E., Yu, K., Cao, J., Wang, M., Katsel, P., Song, W., Wang, Z., Li, Y., Wang, X., Wang, Q., et al. (2025) · Cell · doi:10.1016/j.cell.2025.08.038 · Cited by 44 · see citing works
Self-citationZeng, H., Yu, M., Tan, H., Li, Y., Su, W., Shi, H., Dhungana, Y., Guy, C. S., Neale, G. A. M., Cloer, C., et al. (2018) · Science Advances · doi:10.1126/sciadv.aar5701 · Cited by 44 · see citing works
Self-citationOgata, K., & Ishihama, Y. (2020) · Analytical Chemistry · doi:10.1021/acs.analchem.0c01695 · Cited by 44 · see citing works
Early methionine availability attenuates T cell exhaustion
Sharma, P., Guo, A., Poudel, S., Boada-Romero, E., Verbist, K., Palacios, G., Immadisetty, K., Chen, J., Haydar, D., Mishra, A., et al. (2025) · Nature Immunology · doi:10.1038/s41590-025-02223-6 · Cited by 43 · see citing works
Self-citationLabib, D., Wang, Z., Prakash, P. S., Zimmer, M., Smith, M. D., Frazel, P. W., Barbar, L., Sapar, M. L., Calabresi, P. A., Peng, J., et al. (2022) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2022.870085 · Cited by 42 · see citing works
Self-citationYarbro, J. M., Han, X., Dasgupta, A., Yang, K., Liu, D., Shrestha, H. K., Zaman, M., Wang, Z., Yu, K., Lee, D. G., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-56853-3 · Cited by 41 · see citing works
Self-citationYarbro, J. M., Shrestha, H. K., Wang, Z., Zhang, X., Zaman, M., Chu, M., Wang, X., Yu, G., & Peng, J. (2025) · Molecular Neurodegeneration · doi:10.1186/s13024-025-00874-5 · Cited by 41 · see citing works
Self-citationRegulation of MAGE‐A3/6 by the CRL4‐DCAF12 ubiquitin ligase and nutrient availability
Ravichandran, R., Kodali, K., Peng, J., & Potts, P. R. (2019) · EMBO Reports · doi:10.15252/embr.201847352 · Cited by 39 · see citing works
Self-citationYu, K., Wang, Z., Wu, Z., Tan, H., Mishra, A., & Peng, J. (2021) · Methods in molecular biology · doi:10.1007/978-1-0716-1024-4_15 · Cited by 38 · see citing works
Self-citationZhou, X., Lee, Y.-K., Li, X., Kim, H., Sánchez-Priego, C., Han, X., Tan, H., Zhou, S., Fu, Y., Purtell, K., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-47440-z · Cited by 38 · see citing works
Self-citationDynamic Foxp3–chromatin interaction controls tunable Treg cell function
He, M.-H., Zong, X., Xu, B., Qi, W., Huang, W., Djekidel, M. N., Zhang, Y., Pagala, V., Li, J., Hao, X., et al. (2024) · The Journal of Experimental Medicine · doi:10.1084/jem.20232068 · Cited by 37 · see citing works
Self-citationSun, X., Sun, H., Han, X., Chen, P., Jiao, Y., Wu, Z., Zhang, X., Wang, Z., Niu, M., Yu, K., et al. (2022) · Analytical Chemistry · doi:10.1021/acs.analchem.1c05212 · Cited by 37 · see citing works
Self-citationDeep Profiling of Microgram-Scale Proteome by Tandem Mass Tag Mass Spectrometry
Liu, D., Yang, S., Kavdia, K., Sifford, J. M., Wu, Z., Xie, B., Wang, Z., Pagala, V., Wang, H., Yu, K., et al. (2020) · Journal of Proteome Research · doi:10.1021/acs.jproteome.0c00426 · Cited by 34 · see citing works
Self-citationNovel methods in glycomics: a 2019 update
Cao, W., Liu, M., Kong, S., Wu, M., Huang, Z.-Z., & Yang, P. (2020) · Expert Review of Proteomics · doi:10.1080/14789450.2020.1708199 · Cited by 33 · see citing works
Park, C. S., Yoshihara, H., Gao, Q., Qu, C., Iacobucci, I., Ghate, P. S., Connelly, J. P., Pruett‐Miller, S. M., Wagner, B., Robinson, C. G., et al. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.112804 · Cited by 31 · see citing works
Self-citationWSTF nuclear autophagy regulates chronic but not acute inflammation
Wang, Y., Eapen, V. V., Liang, Y., Kournoutis, A., Sherman, M. S., Xu, Y., Onorati, A., Li, X., Zhou, X., Corey, K. E., et al. (2025) · Nature · doi:10.1038/s41586-025-09234-1 · Cited by 30 · see citing works
Self-citationZaman, M., Fu, Y., Chen, P., Sun, H., Yang, S., Wu, Z., Wang, Z., Poudel, S., Serrano, G. E., Beach, T. G., et al. (2023) · Molecular & Cellular Proteomics · doi:10.1016/j.mcpro.2023.100608 · Cited by 29 · see citing works
Self-citationChen, B., Zhong, X., Yu, F., Snovida, S. I., Xu, M. J., Rogers, J., & Li, L. (2017) · Analytical Chemistry · doi:10.1021/acs.analchem.7b03289 · Cited by 28 · see citing works
Sun, H., Poudel, S., Vanderwall, D., Lee, D. G., Li, Y., & Peng, J. (2022) · PROTEOMICS · doi:10.1002/pmic.202100243 · Cited by 26 · see citing works
Self-citationGenetic regulation of human brain proteome reveals proteins implicated in psychiatric disorders
Luo, J., Li, L., Niu, M., Kong, D., Jiang, Y. W., Poudel, S., Shieh, A. W., Cheng, L., Giase, G. M., Grennan, K. S., et al. (2024) · Molecular Psychiatry · doi:10.1038/s41380-024-02576-8 · Cited by 25 · see citing works
Self-citationAn age-downregulated ribosomal RpS28 protein variant regulates the muscle proteome
Jiao, J., Kavdia, K., Pagala, V., Palmer, L. E., Finkelstein, D., Fan, Y., Peng, J., & Demontis, F. (2021) · G3 Genes Genomes Genetics · doi:10.1093/g3journal/jkab165 · Cited by 24 · see citing works
Self-citationEvaluation of a Dual Isolation Width Acquisition Method for Isobaric Labeling Ratio Decompression
Roumeliotis, T. I., Weisser, H., & Choudhary, J. S. (2018) · Journal of Proteome Research · doi:10.1021/acs.jproteome.8b00870 · Cited by 23 · see citing works
Wang, Z., Kavdia, K., Dey, K. K., Pagala, V., Kodali, K., Liu, D., Lee, D. G., Sun, H., Chepyala, S. R., Cho, J.-H., et al. (2020) · Journal of Visualized Experiments · doi:10.3791/61684 · Cited by 22 · see citing works
Self-citationHKDC1 promotes liver cancer stemness under hypoxia through stabilizing β-catenin
Fan, L., Tian, C. L., Yang, W., Liu, X., Dhungana, Y., Yang, W., Tan, H., Glazer, E. S., Yu, J., Peng, J., et al. (2024) · Hepatology · doi:10.1097/hep.0000000000001085 · Cited by 21 · see citing works
Self-citationTcellSubC: An Atlas of the Subcellular Proteome of Human T Cells
Joshi, R. N., Stadler, C., Lehmann, R., Lehtiö, J., Tegner, J. N., Schmidt, A., & Vesterlund, M. (2019) · Frontiers in Immunology · doi:10.3389/fimmu.2019.02708 · Cited by 21 · see citing works
Rose, C. M., Erickson, B. K., Schweppe, D. K., Viner, R., Choi, J. H., Rogers, J. C., Bomgarden, R. D., Gygi, S. P., & Kirkpatrick, D. S. (2018) · Journal of Proteome Research · doi:10.1021/acs.jproteome.8b00767 · Cited by 19 · see citing works
Proteomic studies of bone and skeletal health outcomes
Nielson, C. M., Jacobs, J., & ORWOLL, E. S. (2019) · Bone · doi:10.1016/j.bone.2019.03.032 · Cited by 19 · see citing works
Chepyala, S. R., Liu, X., Yang, K., Wu, Z., Breuer, A. M., Cho, J.-H., Li, Y., Mancieri, A., Jiao, Y., Zhang, H., et al. (2021) · Analytical Chemistry · doi:10.1021/acs.analchem.1c02309 · Cited by 18 · see citing works
Self-citationHigh, A. A., Tan, H., Pagala, V., Niu, M., Cho, J.-H., Wang, X., Bai, B., & Peng, J. (2017) · Journal of Visualized Experiments · doi:10.3791/56474 · Cited by 18 · see citing works
Self-citationCombining selinexor with alisertib to target the p53 pathway in neuroblastoma
Nguyen, R., Wang, H., Sun, M., Lee, D. G., Peng, J., & Thiele, C. J. (2022) · Neoplasia · doi:10.1016/j.neo.2022.100776 · Cited by 17 · see citing works
Self-citationPoudel, S., Vanderwall, D., Yuan, Z., Wu, Z., Peng, J., & Li, Y. (2022) · PROTEOMICS · doi:10.1002/pmic.202100369 · Cited by 16 · see citing works
Self-citationVanderwall, D., Poudel, S., Fu, Y., Cho, J., Shaw, T. I., Mishra, A., High, A. A., Peng, J., & Li, Y. (2021) · Journal of Visualized Experiments · doi:10.3791/62796 · Cited by 16 · see citing works
Self-citationMulti-omic atlas of the parahippocampal gyrus in Alzheimer’s disease
Coleman, C., Wang, M., Wang, E., Micallef, C., Shao, Z., Vicari, J. M., Li, Y., Yu, K., Cai, D., Peng, J., et al. (2023) · Scientific Data · doi:10.1038/s41597-023-02507-2 · Cited by 16 · see citing works
Self-citationMidkine attenuates amyloid-β fibril assembly and plaque formation
Zaman, M., Yang, S., Huang, Y., Yarbro, J. M., Hao, Y., Wang, Z., Liu, D., Harper, K. E., Soliman, H., Hemphill, A., et al. (2025) · Nature Structural & Molecular Biology · doi:10.1038/s41594-025-01657-8 · Cited by 15 · see citing works
Self-citationYu, K., Niu, M., Wang, H., Li, Y., Wu, Z., Zhang, B., Haroutunian, V. H., & Peng, J. (2021) · Journal of the American Society for Mass Spectrometry · doi:10.1021/jasms.0c00450 · Cited by 15 · see citing works
Self-citationMadern, M., Reiter, W., Stanek, F., Hartl, N., Mechtler, K., & Hartl, M. (2023) · Molecular & Cellular Proteomics · doi:10.1016/j.mcpro.2023.100694 · Cited by 15 · see citing works
Proteomic strategies for characterizing ubiquitin-like modifications
Li, C., Nelson, T., Vertegaal, A. C. O., & Thibault, P. (2021) · Nature Reviews Methods Primers · doi:10.1038/s43586-021-00048-9 · Cited by 14 · see citing works
Proteomic Profiling of Cerebrospinal Fluid by 16-Plex TMT-Based Mass Spectrometry
Dey, K. K., Sun, H., Wang, Z., Niu, M., Wang, H., Jiao, Y., Sun, X., Li, Y., & Peng, J. (2021) · Methods in molecular biology · doi:10.1007/978-1-0716-1936-0_3 · Cited by 14 · see citing works
Self-citationStryiński, R., Mateos, J., Carrera, M., Jastrzebski, J., Bogacka, I., & Łopieńska–Biernat, E. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23084336 · Cited by 13 · see citing works
Experimental and data analysis advances in thermal proteome profiling
Figueroa‐Navedo, A. M., & Ivanov, A. R. (2024) · Cell Reports Methods · doi:10.1016/j.crmeth.2024.100717 · Cited by 13 · see citing works
First-in-Class Small Molecule Degrader of Pregnane X Receptor Enhances Chemotherapy Efficacy
Huber, A. D., Jung, K., Li, Y., Lin, W., Wu, J., Poudel, S., Carrigan, A., Mishra, A., High, A. A., & Chen, T. (2024) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.4c01926 · Cited by 13 · see citing works
Self-citationAn ABC Transporter Drives Medulloblastoma Pathogenesis by Regulating Sonic Hedgehog Signaling
Wijaya, J., Vo, B. T., Liu, J., Xu, B., Wu, G., Wang, Y., Peng, J., Zhang, J., Janke, L. J., Orr, B. A., et al. (2020) · Cancer Research · doi:10.1158/0008-5472.can-19-2054 · Cited by 13 · see citing works
Self-citationMin, J., Yang, S., Cai, Y., Vanderwall, D., Wu, Z., Li, S., Liu, S., Liu, B., Wang, J., Ding, Y., et al. (2023) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-023-04803-x · Cited by 13 · see citing works
Self-citationWright, S., Hu, J., Wang, H., Hyle, J. W., Zhang, Y., Du, G., Konopleva, M. Y., Kornblau, S. M., Djekidel, M. N., Rosikiewicz, W., et al. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2220134120 · Cited by 12 · see citing works
Self-citationShahid, M., Kim, M., Yeon, A., Andres, A. M., You, S., & Kim, J. (2018) · PROTEOMICS · doi:10.1002/pmic.201800190 · Cited by 12 · see citing works
Evaluation of Protein Identification and Quantification by the diaPASEF Method on timsTOF SCP
Wang, J., Tan, H., Fu, Y., Mishra, A., Sun, H., Wang, Z., Wu, Z., Wang, X., Serrano, G. E., Beach, T. G., et al. (2024) · Journal of the American Society for Mass Spectrometry · doi:10.1021/jasms.4c00067 · Cited by 11 · see citing works
Self-citationPan-neurodegeneration proteomics reveals disease subtypes and molecular signatures
Shrestha, H. K., Sun, H., Yarbro, J. M., Lee, D., Liu, D., Wang, E., McReynolds, M. G., Zhang, N., Xie, B., Yang, S., et al. (2026) · Cell · doi:10.1016/j.cell.2026.02.026 · Cited by 11 · see citing works
Self-citationDiffuse leptomeningeal glioneuronal tumor (DLGNT): a comprehensive clinical and molecular analysis
Mikkelsen, M. K., Li, X., Yu, K., High, A. A., Tan, H., Furtado, L. V., Leelatian, N., Bell, J., Berry, J. D., Boué, D. R., et al. (2025) · Acta Neuropathologica · doi:10.1007/s00401-025-02924-0 · Cited by 9 · see citing works
Self-citationToxicoproteomic Profiling of hPXR Transgenic Mice Treated with Rifampicin and Isoniazid
Brewer, C. T., Kodali, K., Wu, J., Shaw, T. I., Peng, J., & Chen, T. (2020) · Cells · doi:10.3390/cells9071654 · Cited by 9 · see citing works
Self-citationImpact of common variants on brain gene expression from RNA to protein to schizophrenia risk
Liang, Q., Jiang, Y., Shieh, A. W., Zhou, D., Chen, R., Wang, F., Xu, M. M., Niu, M., Wang, X., Pinto, D., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-65818-5 · Cited by 9 · see citing works
Self-citationSimple Method to Quantify Protein Abundances from 1000 Cells
Vitrinel, B., Iannitelli, D. E., Mazzoni, E. O., Christiaen, L., & Vogel, C. (2020) · ACS Omega · doi:10.1021/acsomega.0c01191 · Cited by 9 · see citing works
Global Proteomic Profiling of Pediatric AML: A Pilot Study
Nguyen, N., Wu, H., Tan, H., Peng, J., Rubnitz, J. E., Cao, X., Pounds, S. B., & Lamba, J. K. (2021) · Cancers · doi:10.3390/cancers13133161 · Cited by 9 · see citing works
Self-citationStryiński, R., Fiedorowicz, E., Mateos, J., Andronowska, A., Łopieńska–Biernat, E., & Carrera, M. (2025) · Frontiers in Immunology · doi:10.3389/fimmu.2025.1509984 · Cited by 8 · see citing works
Selective identification of epigenetic regulators at methylated genomic sites by SelectID
Qian, W., Jiang, P., Niu, M., Fu, Y., Huang, D., Zhang, D., Liang, Y. J., Wang, Q., Han, Y., Zeng, X., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-59002-y · Cited by 8 · see citing works
Self-citationMierzejewski, K., Stryiński, R., Łopieńska–Biernat, E., Mateos, J., Bogacka, I., & Carrera, M. (2021) · Molecular & Cellular Proteomics · doi:10.1016/j.mcpro.2021.100166 · Cited by 8 · see citing works
SMAP is a pipeline for sample matching in proteogenomics
Li, L., Niu, M., Erickson, A., Luo, J., Rowbotham, K., Guo, K., Huang, H., Li, Y., Jiang, Y. W., Hur, J., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-28411-8 · Cited by 8 · see citing works
Self-citationMicroRNA 3′ ends shorten during adolescent brain maturation
Thomas, K. T., Vermare, A., Egleston, S. O., Wang, Y., Mishra, A., Lin, T., Peng, J., & Zakharenko, S. S. (2023) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2023.1168695 · Cited by 8 · see citing works
Self-citationHuber, A. D., Lin, W., Jung, K., Poudel, S., Yang, G., Wu, J., Carrigan, A., Pagala, V., Wang, W., Fu, Y., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-64773-5 · Cited by 7 · see citing works
Self-citationYang, S., Guo, J., Xiong, Y., Han, G., Luo, T., Peng, S., Liu, J., Hu, T., Zha, Y., Lin, X., et al. (2024) · International Immunopharmacology · doi:10.1016/j.intimp.2024.112420 · Cited by 7 · see citing works
Atashi, M., Jiang, P., Nwaiwu, J. I., Reyes, C. D. G., Nguyen, H. M. T., Li, Y., Ahmadi, P., Purba, W. T., & Mechref, Y. S. (2024) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-024-05352-3 · Cited by 7 · see citing works
Self-citationNiu, W., Yu, S., Li, X., Wang, Z., Chen, R., Michalski, C., Jahangiri, A., Zohdy, Y. M., Chern, J. J., Whitworth, T. J., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.10.07.617121 · Cited by 7 · see citing works
Self-citationO'Reilly, C., Cho, J., Qi, Q., Peters, J. L., Fukuda, Y., Frase, S., Peng, J., Schuetz, J. D., Cheng, Y., Yoon, S.-O., et al. (2019) · Experimental Cell Research · doi:10.1016/j.yexcr.2019.03.028 · Cited by 6 · see citing works
Self-citationCharacterization of a dual degrader of MDM2 and GSPT1
Tandon, I., Esguerra, P. N., Li, C., Sun, H., Yang, K., Zhang, Z., Peng, J., & Tang, W. (2025) · European Journal of Medicinal Chemistry · doi:10.1016/j.ejmech.2025.117793 · Cited by 5 · see citing works
Self-citationZhang, X., Sun, H., Wang, Z., Zhou, S., Fu, Y., High, A. A., & Peng, J. (2023) · Methods in molecular biology · doi:10.1007/978-1-0716-2978-9_8 · Cited by 5 · see citing works
Self-citationTan, H., Blanco, D. B., Xie, B., Li, Y., Wu, Z., Chi, H., & Peng, J. (2021) · Methods in molecular biology · doi:10.1007/978-1-0716-1311-5_23 · Cited by 5 · see citing works
Self-citationEvaluation of a Pooling Chemoproteomics Strategy with an FDA-Approved Drug Library
Sun, H., Yang, K., Zhang, X., Fu, Y., Yarbro, J. M., Wu, Z., Chen, P., Chen, T., & Peng, J. (2022) · Biochemistry · doi:10.1021/acs.biochem.2c00256 · Cited by 5 · see citing works
Self-citationTetraspanin CD82 Correlates with and May Regulate S100A7 Expression in Oral Cancer
Reddi, K. K., Zhang, W., Shahrabi‐Farahani, S., Anderson, K. M., Liu, M., Kakhniashvili, D. G., Wang, X., & Zhang, Y. H. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms25052659 · Cited by 4 · see citing works
Self-citationAlves, G., Ogurtsov, A. Y., Porterfield, H. S., Maity, T. K., Jenkins, L. M. M., Sacks, D. B., & Yu, Y. (2024) · Journal of the American Society for Mass Spectrometry · doi:10.1021/jasms.3c00445 · Cited by 4 · see citing works
Hogrebe, A., Hess, K. N., Llovet, A., Ramos, Y. J., Barente, A. S., Hernandez‐Portugues, D., Smith, I. R. L., Rodríguez‐Mias, R. A., & Villén, J. (2022) · PROTEOMICS · doi:10.1002/pmic.202100253 · Cited by 4 · see citing works
Stable Protein Gel Storage in Acetonitrile for Mass Spectrometric Analysis
Chen, Y., Wang, S., Jia, J., Tian, X., Xu, H., Ning, M., & Bai, B. (2018) · PROTEOMICS · doi:10.1002/pmic.201700336 · Cited by 4 · see citing works
Evaluating cPILOT Data toward Quality Control Implementation
Bowser, B. L., Patterson, K. L., & Robinson, R. A. S. (2023) · Journal of the American Society for Mass Spectrometry · doi:10.1021/jasms.3c00179 · Cited by 3 · see citing works
Shrestha, H. K., Sun, H., Wang, J., & Peng, J. (2024) · Methods in molecular biology · doi:10.1007/978-1-0716-3934-4_10 · Cited by 2 · see citing works
Self-citationDey, K. K., Yarbro, J. M., Liu, D., Han, X., Wang, Z., Jiao, Y., Wu, Z., Yang, S., Lee, D. G., Dasgupta, A., et al. (2023) · Journal of Proteome Research · doi:10.1021/acs.jproteome.3c00496 · Cited by 2 · see citing works
Self-citationTanaka, K., Kondo, A., & Hasunuma, T. (2026) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2600150123 · Cited by 1 · see citing works
Genetic modulation of protein expression in rat brain
Li, L., Wu, Z., Guarracino, A., Villani, F., Kong, D., Mancieri, A., Zhang, A., Saba, L. M., Chen, H., Brožka, H., et al. (2025) · iScience · doi:10.1016/j.isci.2025.112079 · Cited by 1 · see citing works
Self-citation
- Authors
- Niu, M., Cho, J.-H., Kodali, K., Pagala, V., High, A. A., Wang, H., Wu, Z., Li, Y., Bi, W., Zhang, H., Wang, X., Zou, W., & Peng, J.
- Affiliations
- Heilongjiang University of Chinese Medicine (CN)
- St. Jude Children's Research Hospital (US)
- University of Tennessee Health Science Center (US)
- Corresponding author
- Peng, Junmin
- ORCID
- Venue
- Analytical Chemistry
- Publisher
- American Chemical Society (ACS)
- Published
- 2017-02-22
- Volume
- 89
- Issue
- 5
- Pages
- 2956-2963
- ISSN
- 0003-2700 (ISSN-L)
- 1520-6882
- PMC
- PMC5467445
- OpenAlex
- W2587008851
- Cited by
- 118
- References
- 40
- Citations by year
- 2026: 9 · 2025: 16 · 2024: 16 · 2023: 12 · 2022: 13 · 2021: 17 · 2020: 14 · 2019: 9 · 2018: 7 · 2017: 4
- FWCI
- 4.59
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Analytical Chemistry (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute on Aging (R01AG047928, R01AG053987)
- National Institute of General Medical Sciences (R01GM114260)
- American Lebanese Syrian Associated Charities
- 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 › Metabolomics and Mass Spectrometry Studies
- Keywords
- isobaric labeling, tandem mass tags, peptide fractionation, two-dimensional liquid chromatography, MS3, protein quantification
- MeSH terms
- Algorithms, Animals, Brain, Chromatography, High Pressure Liquid, Escherichia coli, Hydrogen-Ion Concentration, Ions, Peptides, Escherichia coli Proteins, Rats, Tandem Mass Spectrometry
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
