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Label‐free profiling of skeletal muscle using high‐definition mass spectrometry
dc.contributor.authorBurniston, Jatin G.en_US
dc.contributor.authorConnolly, Joanneen_US
dc.contributor.authorKainulainen, Heikkien_US
dc.contributor.authorBritton, Steven L.en_US
dc.contributor.authorKoch, Lauren G.en_US
dc.date.accessioned2014-11-04T16:35:07Z
dc.date.availableWITHHELD_12_MONTHSen_US
dc.date.available2014-11-04T16:35:07Z
dc.date.issued2014-10en_US
dc.identifier.citationBurniston, Jatin G.; Connolly, Joanne; Kainulainen, Heikki; Britton, Steven L.; Koch, Lauren G. (2014). "Label‐free profiling of skeletal muscle using high‐definition mass spectrometry." PROTEOMICS 14(20): 2339-2344.en_US
dc.identifier.issn1615-9853en_US
dc.identifier.issn1615-9861en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/109264
dc.publisherDepartments of Environmental Health and Biostatistics, University of Washington, Seattle, WAen_US
dc.publisherWiley Periodicals, Inc.en_US
dc.subject.otherAnimal Proteomicsen_US
dc.subject.otherLC‐MSen_US
dc.subject.otherIon Mobilityen_US
dc.subject.otherData‐Independent Acquisitionen_US
dc.titleLabel‐free profiling of skeletal muscle using high‐definition mass spectrometryen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelMaterials Science and Engineeringen_US
dc.subject.hlbsecondlevelMolecular, Cellular and Developmental Biologyen_US
dc.subject.hlbsecondlevelBiological Chemistryen_US
dc.subject.hlbsecondlevelChemical Engineeringen_US
dc.subject.hlbsecondlevelChemistryen_US
dc.subject.hlbtoplevelHealth Sciencesen_US
dc.subject.hlbtoplevelScienceen_US
dc.subject.hlbtoplevelEngineeringen_US
dc.description.peerreviewedPeer Revieweden_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/109264/1/pmic7807.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/109264/2/pmic7807-sup-0002-FigureS2.pdf
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/109264/3/pmic7807-sup-0001-FigureS1.pdf
dc.identifier.doi10.1002/pmic.201400118en_US
dc.identifier.sourcePROTEOMICSen_US
dc.identifier.citedreferenceShliaha, P. V., Bond, N. J., Gatto, L., Lilley, K. S., Effects of traveling wave ion mobility separation on data independent acquisition in proteomics studies. J. Proteome Res. 2013, 12, 2323 – 2339.en_US
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dc.identifier.citedreferenceLevin, Y., Hradetzky, E., Bahn, S., Quantification of proteins using data‐independent analysis (MSE) in simple and complex samples: a systematic evaluation. Proteomics 2011, 11, 3273 – 3287.en_US
dc.identifier.citedreferenceLi, G. Z., Vissers, J. P., Silva, J. C., Golick, D. et al., Database searching and accounting of multiplexed precursor and product ion spectra from the data independent analysis of simple and complex peptide mixtures. Proteomics 2009, 9, 1696 – 1719.en_US
dc.identifier.citedreferenceMalik, Z., Cobley, J., Morton, J., Close, G. et al., Label‐free LC‐MS profiling of skeletal muscle reveals heart‐type fatty acid binding protein as a candidate biomarker of aerobic capacity. Proteomes 2013, 1, 290 – 308.en_US
dc.identifier.citedreferenceBurniston, J. G., Hoffman, E. P., Proteomic responses of skeletal and cardiac muscle to exercise. Expert Rev. Proteomics 2011, 8, 361 – 377.en_US
dc.identifier.citedreferenceHøjlund, K., Yi, Z., Hwang, H., Bowen, B. et al., Characterization of the human skeletal muscle proteome by one‐dimensional gel electrophoresis and HPLC‐ESI‐MS/MS. Mol. Cell Proteomics 2008, 7, 257 – 267.en_US
dc.identifier.citedreferenceHussey, S. E., Sharoff, C. G., Garnham, A., Zhengping, Y. et al., Effect of exercise on the skeletal muscle proteome in patients with type 2 diabetes. Med. Sci. Sports Exerc. 2012, 45, 1069 – 1076.en_US
dc.identifier.citedreferenceParker, K. C., Walsh, R. J., Salajegheh, M., Amato, A. A. et al., Characterization of human skeletal muscle biopsy samples using shotgun proteomics. J. Proteome Res. 2009, 8, 3265 – 3277.en_US
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 – 156.en_US
dc.identifier.citedreferenceBurniston, J. G., Kenyani, J., Gray, D., Guadagnin, E. et al., Conditional independence mapping of DIGE data reveals PDIA3 protein species as key nodes associated with muscle aerobic capacity. J. Proteomics 2014, 106C, 230 – 245.en_US
dc.identifier.citedreferenceGeiger, T., Velic, A., Macek, B., Lundberg, E. et al., Initial quantitative proteomic map of 28 mouse tissues using the SILAC mouse. Mol. Cell Proteomics 2013, 12, 1709 – 1722.en_US
dc.identifier.citedreferenceDrexler, H. C., Ruhs, A., Konzer, A., Mendler, L. et al., On marathons and Sprints: an integrated quantitative proteomics and transcriptomics analysis of differences between slow and fast muscle fibers. Mol. Cell Proteomics 2012, 11, 1 – 16. M111.010801.en_US
dc.identifier.citedreferencevan Belle, G., Millard, S. P., STRUTS: Statistical Rules of Thumb. Departments of Environmental Health and Biostatistics, University of Washington, Seattle, WA 1998.en_US
dc.identifier.citedreferenceKoh, H. J., Toyoda, T., Fujii, N., Jung, M. M. et al., Sucrose nonfermenting AMPK‐related kinase (SNARK) mediates contraction‐stimulated glucose transport in mouse skeletal muscle. Proc. Natl. Acad. Sci. USA 2010, 107, 15541 – 15546.en_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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