The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Multiplexed MS/MS for improved data-independent acquisition
Open accessAbstract
In mass spectrometry–based proteomics, data-independent acquisition (DIA) strategies can acquire a single data set useful for both identification and quantification of detectable peptides in a complex mixture. However, DIA data are noisy owing to a typical five- to tenfold reduction in precursor selectivity compared to data obtained with data-dependent acquisition or selected reaction monitoring. We demonstrate a multiplexing strategy, MSX, for DIA analysis that increases precursor selectivity fivefold.
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Cites
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Cited by
MS-DIAL: data-independent MS/MS deconvolution for comprehensive metabolome analysis
Tsugawa, H., Cajka, T., Kind, T., Ma, Y., Higgins, B., Ikeda, K., Kanazawa, M., VanderGheynst, J., Fiehn, O., & Arita, M. (2015) · Nature Methods · doi:10.1038/nmeth.3393 · Cited by 3,397
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Current approaches and challenges for the metabolite profiling of complex natural extracts
Wolfender, J.-L., Marti, G., Thomas, A., & Bertrand, S. (2015) · Journal of Chromatography A · doi:10.1016/j.chroma.2014.10.091 · Cited by 635
Carr, S. A., Abbatiello, S. E., Ackermann, B. L., Borchers, C., Domon, B., Deutsch, E. W., Grant, R. P., Hoofnagle, A. N., Hüttenhain, R., Koomen, J. M., et al. (2014) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m113.036095 · Cited by 561
Self-citationVidova, V., & Spacil, Z. (2017) · Analytica Chimica Acta · doi:10.1016/j.aca.2017.01.059 · Cited by 352
Meier, F., Geyer, P. E., Virreira Winter, S., Cox, J., & Mann, M. (2018) · Nature Methods · doi:10.1038/s41592-018-0003-5 · Cited by 348
Collins, B. C., Gillet, L. C., Rosenberger, G., Röst, H. L., Vichalkovski, A., Gstaiger, M., & Aebersold, R. (2013) · Nature Methods · doi:10.1038/nmeth.2703 · Cited by 314
A Review on Quantitative Multiplexed Proteomics
Pappireddi, N., Martin, L., & Wühr, M. (2019) · ChemBioChem · doi:10.1002/cbic.201800650 · Cited by 299
Phosphoproteomics in the Age of Rapid and Deep Proteome Profiling
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Statistical analysis of proteomics data: A review on feature selection
Lualdi, M., & Fasano, M. (2019) · Journal of Proteomics · doi:10.1016/j.jprot.2018.12.004 · Cited by 93
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Metadata
- Authors
- Egertson, J. D., Kuehn, A., Merrihew, G. E., Bateman, N. W., MacLean, B. X., Ting, Y. S., Canterbury, J. D., Marsh, D. M., Kellmann, M., Zabrouskov, V., Wu, C. C., & MacCoss, M. J.
- Venue
- Nature Methods
- Published
- 2013-06-23
- Volume
- 10
- Issue
- 8
- Pages
- 744-746
- ISSN
- 1548-7091 (ISSN-L)
- 1548-7105
- OpenAlex
- W1998295756
- Cited by
- 304
- References
- 3
- FWCI
- 15.28
- Type
- journal article
- Language
- en
- Open access
- green
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