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dc.contributor.author Skinner, Owen S. en
dc.contributor.author Havugimana, Pierre C. en
dc.contributor.author Haverland, Nicole A. en
dc.contributor.author Fornelli, Luca en
dc.contributor.author Early, Bryan P. en
dc.contributor.author Greer, Joseph B. en
dc.contributor.author Fellers, Ryan T. en
dc.contributor.author Durbin, Kenneth R. en
dc.contributor.author Do Vale, Luis H. F. en
dc.contributor.author Melani, Rafael D. en
dc.contributor.author Seckler, Henrique S. en
dc.contributor.author Nelp, Micah T. en
dc.contributor.author Belov, Mikhail E. en
dc.contributor.author Horning, Stevan R. en
dc.contributor.author Makarov, Alexander A. en
dc.contributor.author LeDuc, Richard D. en
dc.contributor.author Bandarian, Vahe en
dc.contributor.author Compton, Philip D. en
dc.contributor.author Kelleher, Neil L. en
dc.date.accessioned 2015-12-16T19:29:05Z en
dc.date.available 2015-12-16T19:29:05Z en
dc.identifier.citation TBD en
dc.identifier.uri http://hdl.handle.net/2022/20564 en
dc.description.abstract Efforts to map the human protein interactome have resulted in information about thousands of multi-protein assemblies housed in public repositories, but the molecular characterization and stoichiometry of their protein subunits remains largely unknown. Here, we report a computational search strategy for hierarchical top-down analysis, identification, and scoring of multi-proteoform complexes by native mass spectrometry. en
dc.description.sponsorship The authors thank members of the Kelleher research group and Prof. V. Wysocki for helpful discussions and advice. O.S.S. is supported by a U. S. National Science Foundation Graduate Research Fellowship (2014171659). P.C.H. is a recipient of a Northwestern University's Chemistry of Life Processes Institute Postdoctoral Fellowship Award. L.H.F.D.V. is supported under CNPq research grant 202011/2012-7 from the Brazilian government. H.S.S is supported under the Science Without Borders scholarship 88888.075416/2013-00 from the Coordination for the Improvement of Higher Education Personnel, under the Brazilian government. This work was supported by grants from the W.M. Keck Foundation (DT061512) and the U.S. National Institutes of Health (GM067193) to N.L.K. en
dc.publisher Nature Publishing Group en
dc.relation.uri http://purl.dlib.indiana.edu/iusw/data/2022/20564/Native_MS_Complex_Search_Tool.zip en
dc.rights Creative Commons Attribution 4.0 en
dc.rights.uri http://creativecommons.org/licenses/by/4.0/ en
dc.subject Native Mass Spectrometry, Proteomics, Protein Complexes en
dc.title An informatic framework for decoding protein complexes by top-down mass spectrometry en
dc.type Dataset en
dc.altmetrics.display false en


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