{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Hemm L"],"funding":["Deutsche Forschungsgemeinschaft (German Research Foundation)","Alexander von Humboldt-Stiftung (Alexander von Humboldt Foundation)"],"pagination":["8527"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12475003"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["16(1)"],"pubmed_abstract":["The computational analysis of large proteomics datasets from gradient profiling or spatially resolved proteomics is often as crucial as experimental design. We present RAPDOR, a tool for intuitive analyzing and visualizing such datasets, based on the Jensen-Shannon distance and analysis of similarities between replicates, applied to the identification of RNA-binding proteins (RBPs) and spatial proteomics. First, we examine the in-gradient distribution profiles of protein complexes with or without RNase treatment (GradR) to identify RBPs in the cyanobacterium Synechocystis 6803. RBPs play pivotal regulatory and structural roles. Although numerous RBPs are well characterized, the complete set of RBPs remains unknown for any species. RAPDOR identifies 165 potential RBPs, including ribosomal p"],"journal":["Nature communications"],"pubmed_title":["RAPDOR: Using Jensen-Shannon Distance for the computational analysis of complex proteomics datasets."],"pmcid":["PMC12475003"],"funding_grant_id":["BA 2168/21-2","322977937/GRK2344","CIBSS - EXC-2189 - Project ID 390939984","BE 3869/5-2","Alexander von Humboldt postdoctoral fellowship","HE 2544/12-2","390939984"],"pubmed_authors":["Becher D","Rabsch D","Hemm L","Bartel J","Gerth P","Backofen R","Ropp HR","Reimann V","Brenes-Alvarez M","Hess WR","Maaß S"],"additional_accession":[]},"is_claimable":false,"name":"RAPDOR: Using Jensen-Shannon Distance for the computational analysis of complex proteomics datasets.","description":"The computational analysis of large proteomics datasets from gradient profiling or spatially resolved proteomics is often as crucial as experimental design. We present RAPDOR, a tool for intuitive analyzing and visualizing such datasets, based on the Jensen-Shannon distance and analysis of similarities between replicates, applied to the identification of RNA-binding proteins (RBPs) and spatial proteomics. First, we examine the in-gradient distribution profiles of protein complexes with or without RNase treatment (GradR) to identify RBPs in the cyanobacterium Synechocystis 6803. RBPs play pivotal regulatory and structural roles. Although numerous RBPs are well characterized, the complete set of RBPs remains unknown for any species. RAPDOR identifies 165 potential RBPs, including ribosomal p","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Sep","modification":"2026-06-03T23:08:53.293Z","creation":"2026-05-02T03:11:51.814Z"},"accession":"S-EPMC12475003","cross_references":{"pubmed":["41006269"],"doi":["10.1038/s41467-025-64086-7"]}}