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CoExpresso: assess the quantitative behavior of protein complexes in human cells
BACKGROUND: Translational and post-translational control mechanisms in the cell result in widely observable differences between measured gene transcription and protein abundances. Herein, protein complexes are among the most tightly controlled entities by selective degradation of their individual pr...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6327379/ https://www.ncbi.nlm.nih.gov/pubmed/30626316 http://dx.doi.org/10.1186/s12859-018-2573-8 |
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author | Chalabi, Morteza H. Tsiamis, Vasileios Käll, Lukas Vandin, Fabio Schwämmle, Veit |
author_facet | Chalabi, Morteza H. Tsiamis, Vasileios Käll, Lukas Vandin, Fabio Schwämmle, Veit |
author_sort | Chalabi, Morteza H. |
collection | PubMed |
description | BACKGROUND: Translational and post-translational control mechanisms in the cell result in widely observable differences between measured gene transcription and protein abundances. Herein, protein complexes are among the most tightly controlled entities by selective degradation of their individual proteins. They furthermore act as control hubs that regulate highly important processes in the cell and exhibit a high functional diversity due to their ability to change their composition and their structure. Better understanding and prediction of these functional states demands methods for the characterization of complex composition, behavior, and abundance across multiple cell states. Mass spectrometry provides an unbiased approach to directly determine protein abundances across different cell populations and thus to profile a comprehensive abundance map of proteins. RESULTS: We provide a tool to investigate the behavior of protein subunits in known complexes by comparing their abundance profiles across up to 140 cell types available in ProteomicsDB. Thorough assessment of different randomization methods and statistical scoring algorithms allows determining the significance of concurrent profiles within a complex, therefore providing insights into the conservation of their composition across human cell types as well as the identification of intrinsic structures in complex behavior to determine which proteins orchestrate complex function. This analysis can be extended to investigate common profiles within arbitrary protein groups. CoExpresso can be accessed through http://computproteomics.bmb.sdu.dk/Apps/CoExpresso. CONCLUSIONS: With the CoExpresso web service, we offer a potent scoring scheme to assess proteins for their co-regulation and thereby offer insight into their potential for forming functional groups like protein complexes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-018-2573-8) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6327379 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-63273792019-01-15 CoExpresso: assess the quantitative behavior of protein complexes in human cells Chalabi, Morteza H. Tsiamis, Vasileios Käll, Lukas Vandin, Fabio Schwämmle, Veit BMC Bioinformatics Software BACKGROUND: Translational and post-translational control mechanisms in the cell result in widely observable differences between measured gene transcription and protein abundances. Herein, protein complexes are among the most tightly controlled entities by selective degradation of their individual proteins. They furthermore act as control hubs that regulate highly important processes in the cell and exhibit a high functional diversity due to their ability to change their composition and their structure. Better understanding and prediction of these functional states demands methods for the characterization of complex composition, behavior, and abundance across multiple cell states. Mass spectrometry provides an unbiased approach to directly determine protein abundances across different cell populations and thus to profile a comprehensive abundance map of proteins. RESULTS: We provide a tool to investigate the behavior of protein subunits in known complexes by comparing their abundance profiles across up to 140 cell types available in ProteomicsDB. Thorough assessment of different randomization methods and statistical scoring algorithms allows determining the significance of concurrent profiles within a complex, therefore providing insights into the conservation of their composition across human cell types as well as the identification of intrinsic structures in complex behavior to determine which proteins orchestrate complex function. This analysis can be extended to investigate common profiles within arbitrary protein groups. CoExpresso can be accessed through http://computproteomics.bmb.sdu.dk/Apps/CoExpresso. CONCLUSIONS: With the CoExpresso web service, we offer a potent scoring scheme to assess proteins for their co-regulation and thereby offer insight into their potential for forming functional groups like protein complexes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-018-2573-8) contains supplementary material, which is available to authorized users. BioMed Central 2019-01-09 /pmc/articles/PMC6327379/ /pubmed/30626316 http://dx.doi.org/10.1186/s12859-018-2573-8 Text en © The Author(s) 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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 | Software Chalabi, Morteza H. Tsiamis, Vasileios Käll, Lukas Vandin, Fabio Schwämmle, Veit CoExpresso: assess the quantitative behavior of protein complexes in human cells |
title | CoExpresso: assess the quantitative behavior of protein complexes in human cells |
title_full | CoExpresso: assess the quantitative behavior of protein complexes in human cells |
title_fullStr | CoExpresso: assess the quantitative behavior of protein complexes in human cells |
title_full_unstemmed | CoExpresso: assess the quantitative behavior of protein complexes in human cells |
title_short | CoExpresso: assess the quantitative behavior of protein complexes in human cells |
title_sort | coexpresso: assess the quantitative behavior of protein complexes in human cells |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6327379/ https://www.ncbi.nlm.nih.gov/pubmed/30626316 http://dx.doi.org/10.1186/s12859-018-2573-8 |
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