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CEDAR, an online resource for the reporting and exploration of complexome profiling data

  • Complexome profiling is an emerging ‘omics approach that systematically interrogates the composition of protein complexes (the complexome) of a sample, by combining biochemical separation of native protein complexes with mass-spectrometry based quantitation proteomics. The resulting fractionation profiles hold comprehensive information on the abundance and composition of the complexome, and have a high potential for reuse by experimental and computational researchers. However, the lack of a central resource that provides access to these data, reported with adequate descriptions and an analysis tool, has limited their reuse. Therefore, we established the ComplexomE profiling DAta Resource (CEDAR, www3.cmbi.umcn.nl/cedar/), an openly accessible database for depositing and exploring mass spectrometry data from complexome profiling studies. Compatibility and reusability of the data is ensured by a standardized data and reporting format containing the “minimum information required for a complexome profiling experiment” (MIACE). The data can be accessed through a user-friendly web interface, as well as programmatically using the REST API portal. Additionally, all complexome profiles available on CEDAR can be inspected directly on the website with the profile viewer tool that allows the detection of correlated profiles and inference of potential complexes. In conclusion, CEDAR is a unique, growing and invaluable resource for the study of protein complex composition and dynamics across biological systems.

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Author:Joeri van StrienORCiD, Alexander HauptORCiDGND, Uwe SchulteORCiDGND, Hans-Peter BraunORCiDGND, Alfredo Cabrera-OreficeORCiD, Jyoti S. ChoudharyORCiD, Felix EversORCiD, Erika Fernandez-VizarraORCiD, Sergio Guerrero-CastilloORCiD, Taco W.A. KooijORCiD, Petra Pálenı́kováORCiD, Mercedes PardoORCiD, Cristina UgaldeORCiD, Ilka WittigORCiD, Lars WöhlbrandGND, Ulrich BrandtORCiDGND, Susanne ArnoldORCiDGND, Martijn A. HuynenORCiD
URN:urn:nbn:de:hebis:30:3-728516
DOI:https://doi.org/10.1101/2020.12.11.421172
Parent Title (English):bioRxiv
Document Type:Preprint
Language:English
Date of Publication (online):2020/12/11
Date of first Publication:2020/12/11
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2023/09/21
Issue:2020.12.11.421172
Page Number:11
HeBIS-PPN:512122520
Institutes:Medizin
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie
Sammlungen:Universitätspublikationen
Licence (German):License LogoCreative Commons - CC BY-NC - Namensnennung - Nicht kommerziell 4.0 International