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Sorting the Muck from the Brass: Analysis of Protein Complexes and Cell Lysates
M. Zoltner, RC. Del Pino, MC. Field
Jazyk angličtina Země Spojené státy americké
Typ dokumentu časopisecké články, práce podpořená grantem
Grantová podpora
MR/P009018/1
Medical Research Council - United Kingdom
MR/N010558/1
Medical Research Council - United Kingdom
MR/P009018/
Medical Research Council - United Kingdom
204697/Z/16/Z
Wellcome Trust - United Kingdom
- MeSH
- datové soubory jako téma MeSH
- elektroforéza v polyakrylamidovém gelu metody MeSH
- hmotnostní spektrometrie metody MeSH
- multiproteinové komplexy izolace a purifikace metabolismus MeSH
- proteomika metody MeSH
- protozoální proteiny izolace a purifikace metabolismus MeSH
- Trypanosoma brucei brucei metabolismus MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Reliable determination of protein complex composition or changes to protein levels in whole cells is challenging. Despite the multitude of methods now available for labeling, analysis, and the statistical processing of data, this large variety is of itself an issue: Which approach is most appropriate, where do you set cutoffs, and what is the most cost-effective strategy? One size does not fit all for such work, but some guidelines can help in terms of reducing cost, improving data quality, and ultimately advancing investigations. Here we describe two protocols and algorithms for facile sample preparation for mass spectrometric analysis, robust data processing, and considerations of how to interpret large proteomic datasets in a productive and robust manner.
Citace poskytuje Crossref.org
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- $a Zoltner, Martin $u School of Life Sciences, University of Dundee, Dundee, UK ; BIOCEV, Department of Parasitology, Faculty of Science, Charles University in Prague, Vestec, Czechia
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- $a Reliable determination of protein complex composition or changes to protein levels in whole cells is challenging. Despite the multitude of methods now available for labeling, analysis, and the statistical processing of data, this large variety is of itself an issue: Which approach is most appropriate, where do you set cutoffs, and what is the most cost-effective strategy? One size does not fit all for such work, but some guidelines can help in terms of reducing cost, improving data quality, and ultimately advancing investigations. Here we describe two protocols and algorithms for facile sample preparation for mass spectrometric analysis, robust data processing, and considerations of how to interpret large proteomic datasets in a productive and robust manner.
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