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dc.contributor.author
Rödiger, Anja
dc.contributor.author
Agne, Birgit
dc.contributor.author
Baerenfaller, Katja
dc.contributor.author
Baginsky, Sacha
dc.contributor.editor
Jorrin-Novo, Jesus V.
dc.contributor.editor
Komatsu, Setsuko
dc.contributor.editor
Weckwerth, Wolfram
dc.contributor.editor
Wienkoop, Stefanie
dc.date.accessioned
2021-07-14T12:21:12Z
dc.date.available
2017-06-11T01:30:30Z
dc.date.available
2021-07-13T13:26:23Z
dc.date.available
2021-07-14T12:21:12Z
dc.date.issued
2014
dc.identifier.isbn
978-1-62703-630-6
en_US
dc.identifier.isbn
978-1-62703-631-3
en_US
dc.identifier.issn
1064-3745
dc.identifier.issn
1940-6029
dc.identifier.other
10.1007/978-1-62703-631-3_20
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/76283
dc.description.abstract
Arabidopsis is the model plant of choice for large-scale proteome analyses, because its genome is well annotated, essentially free of sequencing errors, and relatively small with little redundancy. Furthermore, most Arabidopsis organs are susceptible to standard protein solubilization protocols making protein extraction relatively simple. Many different facets of functional plant proteomics were established with Arabidopsis such as mapping the subcellular proteomes of organelles, proteo-genomic peptide mapping, and numerous studies on the dynamic changes in protein modification and protein abundances. As most standard proteomics technologies are now routinely applied, research interest is increasingly shifting towards the reverse genetic characterization of gene function at the proteome level, i.e., by profiling the quantitative proteome of wild type in comparison with mutant plant tissue. We report here a simple, standardizable protocol for the large-scale comparative quantitative proteome characterization of different Arabidopsis organs based on normalized spectral counting and suggest a statistical framework for data interpretation. Based on existing organellar proteome maps, proteins can be assigned to organelles, thus allowing the identification of organelle-specific responses.
en_US
dc.language.iso
en
en_US
dc.publisher
Humana Press
en_US
dc.subject
Arabidopsis proteomics
en_US
dc.subject
Quantitative plant proteomics
en_US
dc.subject
Spectral counting
en_US
dc.title
Arabidopsis proteomics: A simple and standardizable workflow for quantitative proteome characterization
en_US
dc.type
Book Chapter
dc.date.published
2013-08-22
ethz.book.title
Plant Proteomics
en_US
ethz.journal.title
Methods in Molecular Biology
ethz.journal.volume
1072
en_US
ethz.journal.abbreviated
Methods Mol Biol
ethz.pages.start
275
en_US
ethz.pages.end
288
en_US
ethz.version.edition
Second edition
en_US
ethz.identifier.scopus
ethz.identifier.nebis
000916990
ethz.publication.place
New York, NY
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02030 - Dep. Biologie / Dep. of Biology::02541 - Institut für Molekulare Pflanzenbiologie / Institute of Molecular Plant Biology::03554 - Gruissem, Wilhelm / Gruissem, Wilhelm
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02030 - Dep. Biologie / Dep. of Biology::02541 - Institut für Molekulare Pflanzenbiologie / Institute of Molecular Plant Biology::03554 - Gruissem, Wilhelm / Gruissem, Wilhelm
ethz.date.deposited
2017-06-11T01:31:58Z
ethz.source
ECIT
ethz.identifier.importid
imp593651531b96781560
ethz.ecitpid
pub:120562
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2017-07-18T15:30:13Z
ethz.rosetta.lastUpdated
2022-03-29T10:24:30Z
ethz.rosetta.versionExported
true
ethz.COinS
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