Show simple item record

New targeted approaches for the quantification of dataâ independent acquisition mass spectrometry

dc.contributor.authorBruderer, Roland
dc.contributor.authorSondermann, Julia
dc.contributor.authorTsou, Chih‐chiang
dc.contributor.authorBarrantes‐freer, Alonso
dc.contributor.authorStadelmann, Christine
dc.contributor.authorNesvizhskii, Alexey I.
dc.contributor.authorSchmidt, Manuela
dc.contributor.authorReiter, Lukas
dc.contributor.authorGomez‐varela, David
dc.date.accessioned2017-05-10T17:48:32Z
dc.date.available2018-07-09T17:42:24Zen
dc.date.issued2017-05
dc.identifier.citationBruderer, Roland; Sondermann, Julia; Tsou, Chih‐chiang ; Barrantes‐freer, Alonso ; Stadelmann, Christine; Nesvizhskii, Alexey I.; Schmidt, Manuela; Reiter, Lukas; Gomez‐varela, David (2017). "New targeted approaches for the quantification of dataâ independent acquisition mass spectrometry." PROTEOMICS 17(9): n/a-n/a.
dc.identifier.issn1615-9853
dc.identifier.issn1615-9861
dc.identifier.urihttps://hdl.handle.net/2027.42/136721
dc.publisherWiley Periodicals, Inc.
dc.subject.otherSpectral libraries
dc.subject.otherDataâ independent acquisition
dc.titleNew targeted approaches for the quantification of dataâ independent acquisition mass spectrometry
dc.typeArticleen_US
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelMolecular, Cellular and Developmental Biology
dc.subject.hlbsecondlevelBiological Chemistry
dc.subject.hlbsecondlevelChemical Engineering
dc.subject.hlbsecondlevelChemistry
dc.subject.hlbsecondlevelMaterials Science and Engineering
dc.subject.hlbtoplevelHealth Sciences
dc.subject.hlbtoplevelScience
dc.subject.hlbtoplevelEngineering
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/136721/1/pmic12608.pdf
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/136721/2/pmic12608_am.pdf
dc.identifier.doi10.1002/pmic.201700021
dc.identifier.sourcePROTEOMICS
dc.identifier.citedreferenceFrank, A. M., Monroe, M. E., Shah, A. R., Carver, J. J. et al., Spectral archives: extending spectral libraries to analyze both identified and unidentified spectra. Nat. Methods 2011, 8, 587 â 591.
dc.identifier.citedreferenceWorboys, J. D., Sinclair, J., Yuan, Y., Jorgensen, C., Systematic evaluation of quantotypic peptides for targeted analysis of the human kinome. Nat. Methods 2014, 11, 1041 â 1044.
dc.identifier.citedreferenceZhang, Z., Prediction of lowâ energy collisionâ induced dissociation spectra of peptides. Anal. Chem. 2004, 76, 3908 â 3922.
dc.identifier.citedreferenceRosenberger, G., Koh, C. C., Guo, T., Rost, H. L. et al., A repository of assays to quantify 10,000 human proteins by SWATHâ MS. Sci. Data 2014, 1, 140031.
dc.identifier.citedreferenceTsou, C. C., Avtonomov, D., Larsen, B., Tucholska, M. et al., DIAâ Umpire: comprehensive computational framework for dataâ independent acquisition proteomics. Nat. Methods 2015, 12, 258 â 264, 257 p. following 264.
dc.identifier.citedreferenceSharma, K., Schmitt, S., Bergner, C. G., Tyanova, S. et al., Cell typeâ and brain regionâ resolved mouse brain proteome. Nat. Neurosci. 2015, 18, 1819 â 1831.
dc.identifier.citedreferenceWilhelm, M., Schlegl, J., Hahne, H., Moghaddas Gholami, A. et al., Massâ spectrometryâ based draft of the human proteome. Nature 2014, 509, 582 â 587.
dc.identifier.citedreferenceKim, M. S., Pinto, S. M., Getnet, D., Nirujogi, R. S. et al., A draft map of the human proteome. Nature 2014, 509, 575 â 581.
dc.identifier.citedreferenceToprak, U. H., Gillet, L. C., Maiolica, A., Navarro, P. et al., Conserved peptide fragmentation as a benchmarking tool for mass spectrometers and a discriminating feature for targeted proteomics. Mol. Cell. Proteomics 2014, 13, 2056 â 2071.
dc.identifier.citedreferenceEscher, C., Reiter, L., MacLean, B., Ossola, R. et al., Using iRT, a normalized retention time for more targeted measurement of peptides. Proteomics 2012, 12, 1111 â 1121.
dc.identifier.citedreferenceCox, J., Neuhauser, N., Michalski, A., Scheltema, R. A. et al., Andromeda: a peptide search engine integrated into the MaxQuant environment. J. Proteome Res. 2011, 10, 1794 â 1805.
dc.identifier.citedreferenceCox, J., Mann, M., MaxQuant enables high peptide identification rates, individualized p.p.b.â range mass accuracies and proteomeâ wide protein quantification. Nat. Biotechnol. 2008, 26, 1367 â 1372.
dc.identifier.citedreferenceBruderer, R., Bernhardt, O. M., Gandhi, T., Miladinovic, S. M. et al., Extending the limits of quantitative proteome profiling with dataâ independent acquisition and application to acetaminophen treated 3D liver microtissues. Mol. Cell. Proteomics 2015, 14, 1400 â 1410.
dc.identifier.citedreferenceKelstrup, C. D., Young, C., Lavallee, R., Nielsen, M. L., Olsen, J. V., Optimized fast and sensitive acquisition methods for shotgun proteomics on a quadrupole orbitrap mass spectrometer. J. Proteome Res. 2012, 11, 3487 â 3497.
dc.identifier.citedreferenceWisniewski, J. R., Zielinska, D. F., Mann, M., Comparison of ultrafiltration units for proteomic and Nâ glycoproteomic analysis by the filterâ aided sample preparation method. Anal. Biochem. 2011, 410, 307 â 309.
dc.identifier.citedreferenceOmenn, G. S., Lane, L., Lundberg, E. K., Beavis, R. C. et al., Metrics for the Human Proteome Project 2015: progress on the human proteome and guidelines for highâ confidence protein identification. J. Proteome Res. 2015, 14, 3452 â 3460.
dc.identifier.citedreferenceEgertson, J. D., Kuehn, A., Merrihew, G. E., Bateman, N. W. et al., Multiplexed MS/MS for improved dataâ independent acquisition. Nat. Methods 2013, 10, 744 â 746.
dc.identifier.citedreferenceLi, Y., Zhong, C. Q., Xu, X., Cai, S. et al., Groupâ DIA: analyzing multiple dataâ independent acquisition mass spectrometry data files. Nat. Methods 2015, 12, 1105 â 1106.
dc.identifier.citedreferenceWang, J., Tucholska, M., Knight, J. D., Lambert, J. P. et al., MSPLITâ DIA: sensitive peptide identification for dataâ independent acquisition. Nat. Methods 2015, 12, 1106 â 1108.
dc.identifier.citedreferenceMichalski, A., Cox, J., Mann, M., More than 100,000 detectable peptide species elute in single shotgun proteomics runs but the majority is inaccessible to dataâ dependent LCâ MS/MS. J. Proteome Res. 2011, 10, 1785 â 1793.
dc.identifier.citedreferenceScheltema, R. A., Hauschild, J. P., Lange, O., Hornburg, D. et al., The Q Exactive HF, a Benchtop mass spectrometer with a preâ filter, highâ performance quadrupole and an ultraâ highâ field Orbitrap analyzer. Mol. Cell. Proteomics 2014, 13, 3698 â 3708.
dc.identifier.citedreferenceLiu, H., Sadygov, R. G., Yates, 3rd, J. R., A model for random sampling and estimation of relative protein abundance in shotgun proteomics. Anal. Chem. 2004, 76, 4193 â 4201.
dc.identifier.citedreferenceVenable, J. D., Dong, M. Q., Wohlschlegel, J., Dillin, A., Yates, J. R., Automated approach for quantitative analysis of complex peptide mixtures from tandem mass spectra. Nat. Methods 2004, 1, 39 â 45.
dc.identifier.citedreferenceSilva, J. C., Gorenstein, M. V., Li, G. Z., Vissers, J. P., Geromanos, S. J., Absolute quantification of proteins by LCMSE: a virtue of parallel MS acquisition. Mol. Cell. Proteomics 2006, 5, 144 â 156.
dc.identifier.citedreferencePanchaud, A., Scherl, A., Shaffer, S. A., von Haller, P. D. et al., Precursor acquisition independent from ion count: how to dive deeper into the proteomics ocean. Anal. Chem. 2009, 81, 6481 â 6488.
dc.identifier.citedreferenceCarvalho, P. C., Han, X., Xu, T., Cociorva, D. et al., XDIA: improving on the labelâ free dataâ independent analysis. Bioinformatics 2010, 26, 847 â 848.
dc.identifier.citedreferenceMartinsâ deâ Souza, D., Faca, V. M., Gozzo, F. C., DIA is not a new mass spectrometry acquisition method. Proteomics 2017, 17, 1700017.
dc.identifier.citedreferenceSchubert, O. T., Gillet, L. C., Collins, B. C., Navarro, P. et al., Building highâ quality assay libraries for targeted analysis of SWATH MS data. Nat. Protoc. 2015, 10, 426 â 441.
dc.identifier.citedreferenceSelevsek, N., Chang, C. Y., Gillet, L. C., Navarro, P. et al., Reproducible and consistent quantification of the Saccharomyces cerevisiae proteome by SWATHâ mass spectrometry. Mol. Cell. Proteomics 2015, 14, 739 â 749.
dc.identifier.citedreferenceBruderer, R., Bernhardt, O. M., Gandhi, T., Reiter, L., Highâ precision iRT prediction in the targeted analysis of dataâ independent acquisition and its impact on identification and quantitation. Proteomics 2016, 16, 2246 â 2256.
dc.identifier.citedreferenceWu, J. X., Song, X., Pascovici, D., Zaw, T. et al., SWATH mass spectrometry performance using extended peptide MS/MS assay libraries. Mol. Cell. Proteomics 2016, 15, 2501 â 2514.
dc.owningcollnameInterdisciplinary and Peer-Reviewed


Files in this item

Show simple item record

Remediation of Harmful Language

The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.

Accessibility

If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.