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 pro...
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creator | Chalabi, Morteza H Tsiamis, Vasileios Käll, Lukas Vandin, Fabio Schwämmle, Veit |
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 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. Keywords: Protein complex, Statistics, Co-regulation |
doi_str_mv | 10.1186/s12859-018-2573-8 |
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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 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. Keywords: Protein complex, Statistics, Co-regulation</description><identifier>ISSN: 1471-2105</identifier><identifier>EISSN: 1471-2105</identifier><identifier>DOI: 10.1186/s12859-018-2573-8</identifier><language>eng</language><publisher>BioMed Central Ltd</publisher><subject>Algorithms ; Cells (Biology) ; Characterization ; Genes ; Mass spectrometry ; Observations ; Physiological aspects ; Proteins ; Proteomics ; Spectroscopy ; Technology application ; Transcription (Genetics) ; Web services</subject><ispartof>BMC Bioinformatics, 2019, Vol.20 (1)</ispartof><rights>COPYRIGHT 2019 BioMed Central Ltd.</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>776,780,860,4476,27902</link.rule.ids></links><search><creatorcontrib>Chalabi, Morteza H</creatorcontrib><creatorcontrib>Tsiamis, Vasileios</creatorcontrib><creatorcontrib>Käll, Lukas</creatorcontrib><creatorcontrib>Vandin, Fabio</creatorcontrib><creatorcontrib>Schwämmle, Veit</creatorcontrib><title>CoExpresso: assess the quantitative behavior of protein complexes in human cells</title><title>BMC Bioinformatics</title><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 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. Keywords: Protein complex, Statistics, Co-regulation</description><subject>Algorithms</subject><subject>Cells (Biology)</subject><subject>Characterization</subject><subject>Genes</subject><subject>Mass spectrometry</subject><subject>Observations</subject><subject>Physiological aspects</subject><subject>Proteins</subject><subject>Proteomics</subject><subject>Spectroscopy</subject><subject>Technology application</subject><subject>Transcription (Genetics)</subject><subject>Web services</subject><issn>1471-2105</issn><issn>1471-2105</issn><fulltext>true</fulltext><rsrctype>report</rsrctype><creationdate>2019</creationdate><recordtype>report</recordtype><sourceid/><recordid>eNqVizsOwjAQRC0EEt8D0PkCBm-IiaFDCERJQY9M2BAjJw5Zgzg-Liho0RTz5knD2BTkDEAv5wSJVishQYtEZQuhO2wAaQYiAam6P9xnQ6K7lJBpqQbsuPW7d9MikV9zQxSBhxL542nqYIMJ9oX8gqV5Wd9yX_Cm9QFtzXNfNQ7fSDyO8lmZqNA5GrNeYRzh5NsjNtvvTtuDuBmHZ1sXPrQmj7liZXNfY2Gj3ygNqUzSpVz8ffgA92BOQg</recordid><startdate>20190109</startdate><enddate>20190109</enddate><creator>Chalabi, Morteza H</creator><creator>Tsiamis, Vasileios</creator><creator>Käll, Lukas</creator><creator>Vandin, Fabio</creator><creator>Schwämmle, Veit</creator><general>BioMed Central Ltd</general><scope/></search><sort><creationdate>20190109</creationdate><title>CoExpresso: assess the quantitative behavior of protein complexes in human cells</title><author>Chalabi, Morteza H ; Tsiamis, Vasileios ; Käll, Lukas ; Vandin, Fabio ; Schwämmle, Veit</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-gale_infotracacademiconefile_A5814024603</frbrgroupid><rsrctype>reports</rsrctype><prefilter>reports</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Algorithms</topic><topic>Cells (Biology)</topic><topic>Characterization</topic><topic>Genes</topic><topic>Mass spectrometry</topic><topic>Observations</topic><topic>Physiological aspects</topic><topic>Proteins</topic><topic>Proteomics</topic><topic>Spectroscopy</topic><topic>Technology application</topic><topic>Transcription (Genetics)</topic><topic>Web services</topic><toplevel>online_resources</toplevel><creatorcontrib>Chalabi, Morteza H</creatorcontrib><creatorcontrib>Tsiamis, Vasileios</creatorcontrib><creatorcontrib>Käll, Lukas</creatorcontrib><creatorcontrib>Vandin, Fabio</creatorcontrib><creatorcontrib>Schwämmle, Veit</creatorcontrib></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chalabi, Morteza H</au><au>Tsiamis, Vasileios</au><au>Käll, Lukas</au><au>Vandin, Fabio</au><au>Schwämmle, Veit</au><format>book</format><genre>unknown</genre><ristype>RPRT</ristype><atitle>CoExpresso: assess the quantitative behavior of protein complexes in human cells</atitle><jtitle>BMC Bioinformatics</jtitle><date>2019-01-09</date><risdate>2019</risdate><volume>20</volume><issue>1</issue><issn>1471-2105</issn><eissn>1471-2105</eissn><abstract>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 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. Keywords: Protein complex, Statistics, Co-regulation</abstract><pub>BioMed Central Ltd</pub><doi>10.1186/s12859-018-2573-8</doi></addata></record> |
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source | Springer Nature - Complete Springer Journals; DOAJ Directory of Open Access Journals; EZB-FREE-00999 freely available EZB journals; PubMed Central; PubMed Central Open Access; Springer Nature OA Free Journals |
subjects | Algorithms Cells (Biology) Characterization Genes Mass spectrometry Observations Physiological aspects Proteins Proteomics Spectroscopy Technology application Transcription (Genetics) Web services |
title | CoExpresso: assess the quantitative behavior of protein complexes in human cells |
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