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CoExpresso: assess the quantitative behavior of protein complexes in human cells
Univ Southern Denmark, Dept Biochem & Mol Biol, Campusvej 55, DK-5230 Odense M, Denmark.;Univ Southern Denmark, VILLUM Ctr Bioanalyt Sci, Campusvej 55, DK-5230 Odense M, Denmark..
Univ Southern Denmark, Dept Biochem & Mol Biol, Campusvej 55, DK-5230 Odense M, Denmark.;Univ Southern Denmark, VILLUM Ctr Bioanalyt Sci, Campusvej 55, DK-5230 Odense M, Denmark..
KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH). Royal Inst Technol, Sch Biotechnol, KTH Sci Life Lab, Solna, Sweden..ORCID iD: 0000-0001-5689-9797
Univ Padua, Dept Informat Engn, Padua, Italy..
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2019 (English)In: BMC Bioinformatics, ISSN 1471-2105, E-ISSN 1471-2105, Vol. 20, article id 17Article in journal (Refereed) Published
Abstract [en]

BackgroundTranslational 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.ResultsWe 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.ConclusionsWith 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.

Place, publisher, year, edition, pages
BMC , 2019. Vol. 20, article id 17
Keywords [en]
Protein complex, Statistics, Co-regulation
National Category
Biochemistry and Molecular Biology
Identifiers
URN: urn:nbn:se:kth:diva-242241DOI: 10.1186/s12859-018-2573-8ISI: 000455335900002PubMedID: 30626316Scopus ID: 2-s2.0-85059641401OAI: oai:DiVA.org:kth-242241DiVA, id: diva2:1283732
Note

QC 20190129

Available from: 2019-01-29 Created: 2019-01-29 Last updated: 2019-01-29Bibliographically approved

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Käll, Lukas

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