Statistical elimination of spectral features with large between-run variation enhances quantitative protein-level conclusions in experiments with data-independent spectral acquisition

Detalles Bibliográficos
Autores principales: Cheng, Lin-Yang, Liu, Yansheng, Chang, Ching-Yun, Röst, Hannes, Aebersold, Ruedi, Vitek, Olga
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Meeting Abstract
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4331794/
http://dx.doi.org/10.1186/1471-2105-16-S2-A4
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author Cheng, Lin-Yang
Liu, Yansheng
Chang, Ching-Yun
Röst, Hannes
Aebersold, Ruedi
Vitek, Olga
author_facet Cheng, Lin-Yang
Liu, Yansheng
Chang, Ching-Yun
Röst, Hannes
Aebersold, Ruedi
Vitek, Olga
author_sort Cheng, Lin-Yang
collection PubMed
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spelling pubmed-43317942015-03-19 Statistical elimination of spectral features with large between-run variation enhances quantitative protein-level conclusions in experiments with data-independent spectral acquisition Cheng, Lin-Yang Liu, Yansheng Chang, Ching-Yun Röst, Hannes Aebersold, Ruedi Vitek, Olga BMC Bioinformatics Meeting Abstract BioMed Central 2015-01-28 /pmc/articles/PMC4331794/ http://dx.doi.org/10.1186/1471-2105-16-S2-A4 Text en Copyright © 2015 Cheng et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Meeting Abstract
Cheng, Lin-Yang
Liu, Yansheng
Chang, Ching-Yun
Röst, Hannes
Aebersold, Ruedi
Vitek, Olga
Statistical elimination of spectral features with large between-run variation enhances quantitative protein-level conclusions in experiments with data-independent spectral acquisition
title Statistical elimination of spectral features with large between-run variation enhances quantitative protein-level conclusions in experiments with data-independent spectral acquisition
title_full Statistical elimination of spectral features with large between-run variation enhances quantitative protein-level conclusions in experiments with data-independent spectral acquisition
title_fullStr Statistical elimination of spectral features with large between-run variation enhances quantitative protein-level conclusions in experiments with data-independent spectral acquisition
title_full_unstemmed Statistical elimination of spectral features with large between-run variation enhances quantitative protein-level conclusions in experiments with data-independent spectral acquisition
title_short Statistical elimination of spectral features with large between-run variation enhances quantitative protein-level conclusions in experiments with data-independent spectral acquisition
title_sort statistical elimination of spectral features with large between-run variation enhances quantitative protein-level conclusions in experiments with data-independent spectral acquisition
topic Meeting Abstract
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4331794/
http://dx.doi.org/10.1186/1471-2105-16-S2-A4
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