{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Declercq A"],"funding":["CHIST-ERA","Bundesministerium für Bildung und Forschung","Deutsche Forschungsgemeinschaft","SFRI-STRAT’US project","Deutschen Konsortium für Translationale Krebsforschung","Fonds Wetenschappelijk Onderzoek","Deutsche Krebshilfe","IdEx Unistra","Heidelberger Zentrum für Personalisierte Onkologie Deutsches Krebsforschungszentrum In Der Helmholtz-Gemeinschaft","French proteomics infrastructure","Universiteit Gent","HORIZON Europe Project BAXERNA 2.0"],"pagination":["1067-1076"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11894666"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["24(3)"],"pubmed_abstract":["The high throughput analysis of proteins with mass spectrometry (MS) is highly valuable for understanding human biology, discovering disease biomarkers, identifying therapeutic targets, and exploring pathogen interactions. To achieve these goals, specialized proteomics subfields, including plasma proteomics, immunopeptidomics, and metaproteomics, must tackle specific analytical challenges, such as an increased identification ambiguity compared to routine proteomics experiments. Technical advancements in MS instrumentation can mitigate these issues by acquiring more discerning information at higher sensitivity levels. This is exemplified by the incorporation of ion mobility and parallel accumulation and serial fragmentation (PASEF) technologies in timsTOF instruments. In addition, AI-based "],"journal":["Journal of proteome research"],"pubmed_title":["TIMS<sup>2</sup>Rescore: A Data Dependent Acquisition-Parallel Accumulation and Serial Fragmentation-Optimized Data-Driven Rescoring Pipeline Based on MS<sup>2</sup>Rescore."],"pmcid":["PMC11894666"],"funding_grant_id":["1286824N","1SE3724N","ANR-10-INBS-08-03","2022_EKSE.79","ANR-10-IDEX-0002","G028821N","101080544","161L0218A/B","ANR-20-SFRI-0012","12A6L24N","G010023N","1SH9O24N","SFB1292 TPQ01","EXC2180-390900677","70114948","12B7123N","BOF21/GOA/033","16LW0241K"],"pubmed_authors":["Preikschat A","Gomez-Zepeda D","Carapito C","Rijal JB","Krieger JR","Martens L","Declercq A","Rosenberger G","Martelli C","Hirschler A","Bouwmeester R","Srikumar T","Gabriels R","Tenzer S","Devreese R","Scheid J","Van Den Bossche T","Degroeve S","Jachmann C","Trede D","Walz JS"],"additional_accession":[]},"is_claimable":false,"name":"TIMS<sup>2</sup>Rescore: A Data Dependent Acquisition-Parallel Accumulation and Serial Fragmentation-Optimized Data-Driven Rescoring Pipeline Based on MS<sup>2</sup>Rescore.","description":"The high throughput analysis of proteins with mass spectrometry (MS) is highly valuable for understanding human biology, discovering disease biomarkers, identifying therapeutic targets, and exploring pathogen interactions. To achieve these goals, specialized proteomics subfields, including plasma proteomics, immunopeptidomics, and metaproteomics, must tackle specific analytical challenges, such as an increased identification ambiguity compared to routine proteomics experiments. Technical advancements in MS instrumentation can mitigate these issues by acquiring more discerning information at higher sensitivity levels. This is exemplified by the incorporation of ion mobility and parallel accumulation and serial fragmentation (PASEF) technologies in timsTOF instruments. In addition, AI-based ","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Mar","modification":"2026-06-02T19:18:39.162Z","creation":"2025-04-04T02:51:04.337Z"},"accession":"S-EPMC11894666","cross_references":{"pubmed":["39915959"],"doi":["10.1021/acs.jproteome.4c00609"]}}