TY - INPR A1 - Strien, Joeri van A1 - Haupt, Alexander A1 - Schulte, Uwe A1 - Braun, Hans-Peter A1 - Cabrera-Orefice, Alfredo A1 - Choudhary, Jyoti S. A1 - Evers, Felix A1 - Fernandez-Vizarra, Erika A1 - Guerrero-Castillo, Sergio A1 - Kooij, Taco W.A. A1 - Pálenı́ková, Petra A1 - Pardo, Mercedes A1 - Ugalde, Cristina A1 - Wittig, Ilka A1 - Wöhlbrand, Lars A1 - Brandt, Ulrich A1 - Arnold, Susanne A1 - Huynen, Martijn A. T1 - CEDAR, an online resource for the reporting and exploration of complexome profiling data T2 - bioRxiv N2 - 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. Y1 - 2020 UR - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/72851 UR - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-728516 IS - 2020.12.11.421172 ER -