The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
The MaxQuant computational platform for mass spectrometry-based shotgun proteomics
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Citations
Cites
Cox, J., & Mann, M. (2008) · Nature Biotechnology · doi:10.1038/nbt.1511 · Cited by 14,855
Self-citationGlobal quantification of mammalian gene expression control
Schwanhäusser, B., Busse, D., Li, N., Dittmar, G., Schuchhardt, J., Wolf, J., Chen, W., & Selbach, M. (2011) · Nature · doi:10.1038/nature10098 · Cited by 6,566 · cited 2×
“44| Set the minimum FDR at which a protein group should be accepted.”
BackgroundCox, J., Hein, M. Y., Luber, C. A., Paron, I., Nagaraj, N., & Mann, M. (2014) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m113.031591 · Cited by 5,180
Self-citationRoss, 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
Elias, J. E., & Gygi, S. P. (2007) · Nature Methods · doi:10.1038/nmeth1019 · Cited by 3,925
McAlister, 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
Geiger, T., Wehner, A., Schaab, C., Cox, J., & Mann, M. (2012) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m111.014050 · Cited by 797
Self-citationA “Proteomic Ruler” for Protein Copy Number and Concentration Estimation without Spike-in Standards
Wiśniewski, J. R., Hein, M. Y., Cox, J., & Mann, M. (2014) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m113.037309 · Cited by 690
Self-citationMichalski, A., Cox, J., & Mann, M. (2011) · Journal of Proteome Research · doi:10.1021/pr101060v · Cited by 685
Self-citationIncreasing the Multiplexing Capacity of TMTs Using Reporter Ion Isotopologues with Isobaric Masses
McAlister, G. C., Huttlin, E. L., Haas, W., Ting, L., Jedrychowski, M. P., Rogers, J. C., Kuhn, K., Pike, I., Grothe, R. A., Blethrow, J. D., et al. (2012) · Analytical Chemistry · doi:10.1021/ac301572t · Cited by 605
Research works printed but not linked: 31
- Hein, M.Y., Sharma, K., Cox, J. & Mann, M. in Handbook of Systems Biology (eds. Walhout, A.J.M., Vidal, M. & Dekker, J.) 3–25 (Academic Press, San Diego, CA, 2013). · DOI
- Cox, J. & Mann, M. Quantitative, high-resolution proteomics for data-driven systems biology. Annu. Rev. Biochem. 80, 273–299 (2011). · DOI · Paper page
- Neuhauser, N., Michalski, A., Cox, J. & Mann, M. Expert system for computer-assisted annotation of MS/MS spectra. Mol. Cell. Proteomics 11, 1500–1509 (2012). · DOI
- Tyanova, S. et al. Visualization of LC–MS/MS proteomics data in MaxQuant. Proteomics 15, 1453–1456 (2015). · DOI · Paper page
- Cox, J. & Mann, M. Computational principles of determining and improving mass precision and accuracy for proteome measurements in an Orbitrap. J. Am. Soc. Mass Spectrom. 20, 1477–1485 (2009). · DOI
- Cox, J., Michalski, A. & Mann, M. Software lock mass by two-dimensional minimization of peptide mass errors. J. Am. Soc. Mass Spectrom. 22, 1373–1380 (2011). · DOI
- Cox, J. et al. Andromeda: a peptide search engine integrated into the MaxQuant environment. J. Proteome Res. 10, 1794–1805 (2011). · DOI
- Olsen, J.V. et al. Higher-energy C-trap dissociation for peptide modification analysis. Nat. Methods 4, 709–712 (2007). · DOI · Paper page
- Michalski, A., Neuhauser, N., Cox, J. & Mann, M. A systematic investigation into the nature of tryptic HCD spectra. J. Proteome Res. 11, 5479–5491 (2012). · DOI
- Mikesh, L.M. et al. The utility of ETD mass spectrometry in proteomic analysis. Biochim. Biophys. Acta 1764, 1811–1822 (2006). · DOI · Paper page
- Frese, C.K. et al. Unambiguous phosphosite localization using electron-transfer/higher-energy collision dissociation (EThcD). J. Proteome Res. 12, 1520–1525 (2013). · DOI
- Spivak, M., Weston, J., Bottou, L., Kall, L. & Noble, W.S. Improvements to the percolator algorithm for peptide identification from shotgun proteomics data sets. J. Proteome Res. 8, 3737–3745 (2009). · DOI · Paper page
- Tyanova, S., Mann, M. & Cox, J. MaxQuant for in-depth analysis of large SILAC datasets. Methods Mol. Biol. 1188, 351–364 (2014). · DOI
- Boersema, P.J., Raijmakers, R., Lemeer, S., Mohammed, S. & Heck, A.J. Multiplex peptide stable isotope dimethyl labeling for quantitative proteomics. Nat. Protoc. 4, 484–494 (2009). · DOI · Paper page
- Thompson, A. et al. Tandem mass tags: a novel quantification strategy for comparative analysis of complex protein mixtures by MS/MS. Anal. Chem. 75, 1895–1904 (2003). · DOI · Paper page
- Imamura, H., Wakabayashi, M. & Ishihama, Y. Analytical strategies for shotgun phosphoproteomics: status and prospects. Semin. Cell Dev. Biol. 23, 836–842 (2012). · DOI
- Zhou, H. et al. Enhancing the identification of phosphopeptides from putative basophilic kinase substrates using Ti (IV) based IMAC enrichment. Mol. Cell. Proteomics 10, M110 006452 (2011). · DOI
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- Savitski, M.M., Nielsen, M.L. & Zubarev, R.A. ModifiComb, a new proteomic tool for mapping substoichiometric post-translational modifications, finding novel types of modifications, and fingerprinting complex protein mixtures. Mol. Cell. Proteomics 5, 935–948 (2006). · DOI
- Chick, J.M. et al. A mass-tolerant database search identifies a large proportion of unassigned spectra in shotgun proteomics as modified peptides. Nat. Biotechnol. 33, 743–749 (2015). · DOI · Paper page
- Neuhauser, N. et al. High performance computational analysis of large-scale proteome data sets to assess incremental contribution to coverage of the human genome. J. Proteome Res. 12, 2858–2868 (2013). · DOI
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- Deeb, S.J. et al. Machine learning based classification of diffuse large B-cell lymphoma patients by their protein expression profiles. Mol. Cell. Proteomics 14, 2947–2960 (2015). · DOI
- Cox, J. & Mann, M. 1D and 2D annotation enrichment: a statistical method integrating quantitative proteomics with complementary high-throughput data. BMC Bioinformatics 13 (Suppl. 16), S12 (2012). · DOI · Paper page
- Robles, M.S., Cox, J. & Mann, M. In-vivo quantitative proteomics reveals a key contribution of post-transcriptional mechanisms to the circadian regulation of liver metabolism. PLoS Genet. 10, e1004047 (2014). · DOI · Paper page
- Geiger, T., Cox, J. & Mann, M. Proteomics on an Orbitrap benchtop mass spectrometer using all-ion fragmentation. Mol. Cell. Proteomics 9, 2252–2261 (2010). · DOI · Paper page
- MacLean, B. et al. Skyline: an open source document editor for creating and analyzing targeted proteomics experiments. Bioinformatics 26, 966–968 (2010). · DOI · Paper page
- Keshishian, H. et al. Multiplexed, quantitative workflow for sensitive biomarker discovery in plasma yields novel candidates for early myocardial injury. Mol. Cell. Proteomics 14, 2375–2393 (2015). · DOI
- Chen, Z.A., Fischer, L., Cox, J. & Rappsilber, J. Quantitative cross-linking/mass spectrometry using isotope-labeled cross-linkers and MaxQuant. Mol. Cell. Proteomics (2016). · DOI
- Nesvizhskii, A.I., Keller, A., Kolker, E. & Aebersold, R. A statistical model for identifying proteins by tandem mass spectrometry. Anal. Chem. 75, 4646–4658 (2003). · DOI · Paper page
- Olsen, J.V. et al. Quantitative phosphoproteomics reveals widespread full phosphorylation site occupancy during mitosis. Sci. Signal. 3, ra3 (2010). · DOI · Paper page
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Lysosome-targeting chimaeras for degradation of extracellular proteins
Banik, S. M., Pedram, K., Wisnovsky, S., Ahn, G., Riley, N. M., & Bertozzi, C. R. (2020) · Nature · doi:10.1038/s41586-020-2545-9 · Cited by 1,199
Integrated Proteogenomic Characterization of HBV-Related Hepatocellular Carcinoma
Gao, Q., Zhu, H., Dong, L., Shi, W., Chen, R., Song, Z., Huang, C., Li, J., Dong, X., Zhou, Y., et al. (2019) · Cell · doi:10.1016/j.cell.2019.08.052 · Cited by 1,096
Budnik, B., Levy, E., Harmange, G., & Slavov, N. (2018) · Genome Biology · doi:10.1186/s13059-018-1547-5 · Cited by 832
Functional characterization of the dural sinuses as a neuroimmune interface
Rustenhoven, J., Drieu, A., Mamuladze, T., de Lima, K. A., Dykstra, T., Wall, M., Papadopoulos, Z., Kanamori, M., Salvador, A. F., Baker, W., et al. (2021) · Cell · doi:10.1016/j.cell.2020.12.040 · Cited by 685
Yoon, H. S., Cho, C. H., Yun, M. S., Jang, S. J., You, H. J., Kim, J.-H., Han, D., Cha, K. H., Moon, S. H., Lee, K., et al. (2021) · Nature Microbiology · doi:10.1038/s41564-021-00880-5 · Cited by 602
Metadata
- Authors
- Tyanova, S., Temu, T., & Cox, J.
- Venue
- Nature Protocols
- Published
- 2016-10-27
- Volume
- 11
- Issue
- 12
- Pages
- 2301-2319
- ISSN
- 1750-2799 (ISSN-L)
- 1754-2189
- OpenAlex
- W2544360569
- Cited by
- 4,797
- References
- 14
- FWCI
- 86.78
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- www.springer.com/tdm (vor)
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