Reproducible quantitative proteotype data matrices for systems biology
Historically, many mass spectrometry–based proteomic studies have aimed at compiling an inventory of protein compounds present in a biological sample, with the long-term objective of creating a proteome map of a species. However, to answer fundamental questions about the behavior of biological syste...
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The American Society for Cell Biology
2015
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| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4710225/ |
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pubmed-47102252016-01-20 Reproducible quantitative proteotype data matrices for systems biology Röst, Hannes L. Malmström, Lars Aebersold, Ruedi Perspectives Historically, many mass spectrometry–based proteomic studies have aimed at compiling an inventory of protein compounds present in a biological sample, with the long-term objective of creating a proteome map of a species. However, to answer fundamental questions about the behavior of biological systems at the protein level, accurate and unbiased quantitative data are required in addition to a list of all protein components. Fueled by advances in mass spectrometry, the proteomics field has thus recently shifted focus toward the reproducible quantification of proteins across a large number of biological samples. This provides the foundation to move away from pure enumeration of identified proteins toward quantitative matrices of many proteins measured across multiple samples. It is argued here that data matrices consisting of highly reproducible, quantitative, and unbiased proteomic measurements across a high number of conditions, referred to here as quantitative proteotype maps, will become the fundamental currency in the field and provide the starting point for downstream biological analysis. Such proteotype data matrices, for example, are generated by the measurement of large patient cohorts, time series, or multiple experimental perturbations. They are expected to have a large effect on systems biology and personalized medicine approaches that investigate the dynamic behavior of biological systems across multiple perturbations, time points, and individuals. The American Society for Cell Biology 2015-11-05 /pmc/articles/PMC4710225/ /pubmed/26543201 http://dx.doi.org/10.1091/mbc.E15-07-0507 Text en © 2015 Röst et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0). “ASCB®,” “The American Society for Cell Biology®,” and “Molecular Biology of the Cell®” are registered trademarks of The American Society for Cell Biology. |
| repository_type |
Open Access Journal |
| institution_category |
Foreign Institution |
| institution |
US National Center for Biotechnology Information |
| building |
NCBI PubMed |
| collection |
Online Access |
| language |
English |
| format |
Online |
| author |
Röst, Hannes L. Malmström, Lars Aebersold, Ruedi |
| spellingShingle |
Röst, Hannes L. Malmström, Lars Aebersold, Ruedi Reproducible quantitative proteotype data matrices for systems biology |
| author_facet |
Röst, Hannes L. Malmström, Lars Aebersold, Ruedi |
| author_sort |
Röst, Hannes L. |
| title |
Reproducible quantitative proteotype data matrices for systems biology |
| title_short |
Reproducible quantitative proteotype data matrices for systems biology |
| title_full |
Reproducible quantitative proteotype data matrices for systems biology |
| title_fullStr |
Reproducible quantitative proteotype data matrices for systems biology |
| title_full_unstemmed |
Reproducible quantitative proteotype data matrices for systems biology |
| title_sort |
reproducible quantitative proteotype data matrices for systems biology |
| description |
Historically, many mass spectrometry–based proteomic studies have aimed at compiling an inventory of protein compounds present in a biological sample, with the long-term objective of creating a proteome map of a species. However, to answer fundamental questions about the behavior of biological systems at the protein level, accurate and unbiased quantitative data are required in addition to a list of all protein components. Fueled by advances in mass spectrometry, the proteomics field has thus recently shifted focus toward the reproducible quantification of proteins across a large number of biological samples. This provides the foundation to move away from pure enumeration of identified proteins toward quantitative matrices of many proteins measured across multiple samples. It is argued here that data matrices consisting of highly reproducible, quantitative, and unbiased proteomic measurements across a high number of conditions, referred to here as quantitative proteotype maps, will become the fundamental currency in the field and provide the starting point for downstream biological analysis. Such proteotype data matrices, for example, are generated by the measurement of large patient cohorts, time series, or multiple experimental perturbations. They are expected to have a large effect on systems biology and personalized medicine approaches that investigate the dynamic behavior of biological systems across multiple perturbations, time points, and individuals. |
| publisher |
The American Society for Cell Biology |
| publishDate |
2015 |
| url |
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4710225/ |
| _version_ |
1613523220915290112 |