{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Birklbauer MJ"],"funding":["Österreichische Forschungsförderungsgesellschaft","Austrian Science Fund FWF","Österreichische Forschungsförderungsgesellschaft (Austrian Research Promotion Agency)","Vienna Science and Technology Fund (Wiener Wissenschafts-, Forschungs- und Technologiefonds)","Vienna Science and Technology Fund"],"pagination":["300"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11659399"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["7(1)"],"pubmed_abstract":["The field of crosslinking mass spectrometry has seen substantial advancements over the past decades, enabling the structural analysis of proteins and protein complexes and serving as a powerful tool in protein-protein interaction studies. However, data analysis of large non-cleavable crosslink studies is still a mostly unsolved problem due to its n-squared complexity. We here introduce an algorithm for the identification of non-cleavable crosslinks implemented in our crosslinking search engine MS Annika that is based on sparse matrix multiplication and allows for proteome-wide searches on commodity hardware. We compare our algorithm to other state-of-the-art crosslinking search engines commonly used in the field and conclude that MS Annika unifies high sensitivity, accurate FDR estimation "],"journal":["Communications chemistry"],"pubmed_title":["Proteome-wide non-cleavable crosslink identification with MS Annika 3.0 reveals the structure of the C. elegans Box C/D complex."],"pmcid":["PMC11659399"],"funding_grant_id":["LS20-079","ESP566","AT-SCP","SFB F 8805-B","P35045-B"],"pubmed_authors":["Birklbauer MJ","Geetha SS","Muller F","Mechtler K","Dorfer V","Matzinger M"],"additional_accession":[]},"is_claimable":false,"name":"Proteome-wide non-cleavable crosslink identification with MS Annika 3.0 reveals the structure of the C. elegans Box C/D complex.","description":"The field of crosslinking mass spectrometry has seen substantial advancements over the past decades, enabling the structural analysis of proteins and protein complexes and serving as a powerful tool in protein-protein interaction studies. However, data analysis of large non-cleavable crosslink studies is still a mostly unsolved problem due to its n-squared complexity. We here introduce an algorithm for the identification of non-cleavable crosslinks implemented in our crosslinking search engine MS Annika that is based on sparse matrix multiplication and allows for proteome-wide searches on commodity hardware. We compare our algorithm to other state-of-the-art crosslinking search engines commonly used in the field and conclude that MS Annika unifies high sensitivity, accurate FDR estimation ","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Dec","modification":"2026-06-01T17:38:10.957Z","creation":"2025-04-04T02:46:50.285Z"},"accession":"S-EPMC11659399","cross_references":{"pubmed":["39702463"],"doi":["10.1038/s42004-024-01386-x"]}}