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Informed-Proteomics: Open Source Software Package for Top-down Proteomics

Top-down proteomics is the analysis of intact proteins in their endogenous form without proteolysis, preserving valuable information about post-translation modifications, isoforms and proteolytic processing. The quality of top-down LC-MS/MS datasets is rapidly increasing due to advances in instrumen...

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Autores principales: Park, Jungkap, Piehowski, Paul D., Wilkins, Christopher, Zhou, Mowei, Mendoza, Joshua, Fujimoto, Grant M, Gibbons, Bryson C., Shaw, Jared B., Shen, Yufeng, Shukla, Anil K., Moore, Ronald J., Liu, Tao, Petyuk, Vladislav A, Tolic, Nikola, Pasa-Tolic, Ljiljana, Smith, Richard D., Payne, Samuel H., Kim, Sangtae
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5578875/
https://www.ncbi.nlm.nih.gov/pubmed/28783154
http://dx.doi.org/10.1038/nmeth.4388
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author Park, Jungkap
Piehowski, Paul D.
Wilkins, Christopher
Zhou, Mowei
Mendoza, Joshua
Fujimoto, Grant M
Gibbons, Bryson C.
Shaw, Jared B.
Shen, Yufeng
Shukla, Anil K.
Moore, Ronald J.
Liu, Tao
Petyuk, Vladislav A
Tolic, Nikola
Pasa-Tolic, Ljiljana
Smith, Richard D.
Payne, Samuel H.
Kim, Sangtae
author_facet Park, Jungkap
Piehowski, Paul D.
Wilkins, Christopher
Zhou, Mowei
Mendoza, Joshua
Fujimoto, Grant M
Gibbons, Bryson C.
Shaw, Jared B.
Shen, Yufeng
Shukla, Anil K.
Moore, Ronald J.
Liu, Tao
Petyuk, Vladislav A
Tolic, Nikola
Pasa-Tolic, Ljiljana
Smith, Richard D.
Payne, Samuel H.
Kim, Sangtae
author_sort Park, Jungkap
collection PubMed
description Top-down proteomics is the analysis of intact proteins in their endogenous form without proteolysis, preserving valuable information about post-translation modifications, isoforms and proteolytic processing. The quality of top-down LC-MS/MS datasets is rapidly increasing due to advances in instrumentation and sample processing protocols. However, the top-down mass spectra are substantially more complex compared to conventional bottom-up data. To take full advantage of the increasing data quality, there is an urgent need to develop algorithms and software tools for confident proteoform identification and quantification. In this study, we present a new open source software suite for top-down proteomics analysis consisting of an LC-MS feature finding algorithm, a database search algorithm, and an interactive results viewer. The presented tool along with several other popular tools were evaluated using human-in-mouse xenograft luminal and basal breast tumor samples that are known to have significant differences in protein abundance based on bottom-up analysis.
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spelling pubmed-55788752018-02-07 Informed-Proteomics: Open Source Software Package for Top-down Proteomics Park, Jungkap Piehowski, Paul D. Wilkins, Christopher Zhou, Mowei Mendoza, Joshua Fujimoto, Grant M Gibbons, Bryson C. Shaw, Jared B. Shen, Yufeng Shukla, Anil K. Moore, Ronald J. Liu, Tao Petyuk, Vladislav A Tolic, Nikola Pasa-Tolic, Ljiljana Smith, Richard D. Payne, Samuel H. Kim, Sangtae Nat Methods Article Top-down proteomics is the analysis of intact proteins in their endogenous form without proteolysis, preserving valuable information about post-translation modifications, isoforms and proteolytic processing. The quality of top-down LC-MS/MS datasets is rapidly increasing due to advances in instrumentation and sample processing protocols. However, the top-down mass spectra are substantially more complex compared to conventional bottom-up data. To take full advantage of the increasing data quality, there is an urgent need to develop algorithms and software tools for confident proteoform identification and quantification. In this study, we present a new open source software suite for top-down proteomics analysis consisting of an LC-MS feature finding algorithm, a database search algorithm, and an interactive results viewer. The presented tool along with several other popular tools were evaluated using human-in-mouse xenograft luminal and basal breast tumor samples that are known to have significant differences in protein abundance based on bottom-up analysis. 2017-08-07 2017-09 /pmc/articles/PMC5578875/ /pubmed/28783154 http://dx.doi.org/10.1038/nmeth.4388 Text en Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms
spellingShingle Article
Park, Jungkap
Piehowski, Paul D.
Wilkins, Christopher
Zhou, Mowei
Mendoza, Joshua
Fujimoto, Grant M
Gibbons, Bryson C.
Shaw, Jared B.
Shen, Yufeng
Shukla, Anil K.
Moore, Ronald J.
Liu, Tao
Petyuk, Vladislav A
Tolic, Nikola
Pasa-Tolic, Ljiljana
Smith, Richard D.
Payne, Samuel H.
Kim, Sangtae
Informed-Proteomics: Open Source Software Package for Top-down Proteomics
title Informed-Proteomics: Open Source Software Package for Top-down Proteomics
title_full Informed-Proteomics: Open Source Software Package for Top-down Proteomics
title_fullStr Informed-Proteomics: Open Source Software Package for Top-down Proteomics
title_full_unstemmed Informed-Proteomics: Open Source Software Package for Top-down Proteomics
title_short Informed-Proteomics: Open Source Software Package for Top-down Proteomics
title_sort informed-proteomics: open source software package for top-down proteomics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5578875/
https://www.ncbi.nlm.nih.gov/pubmed/28783154
http://dx.doi.org/10.1038/nmeth.4388
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