{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Zulfiqar M"],"funding":["Deutsche Forschungsgemeinschaft","Friedrich-Schiller-Universität Jena"],"pagination":["32"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9985203"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["15(1)"],"pubmed_abstract":["Mapping the chemical space of compounds to chemical structures remains a challenge in metabolomics. Despite the advancements in untargeted liquid chromatography-mass spectrometry (LC-MS) to achieve a high-throughput profile of metabolites from complex biological resources, only a small fraction of these metabolites can be annotated with confidence. Many novel computational methods and tools have been developed to enable chemical structure annotation to known and unknown compounds such as in silico generated spectra and molecular networking. Here, we present an automated and reproducible Metabolome Annotation Workflow (MAW) for untargeted metabolomics data to further facilitate and automate the complex annotation by combining tandem mass spectrometry (MS<sup>2</sup>) input data pre-processi"],"journal":["Journal of cheminformatics"],"pubmed_title":["MAW: the reproducible Metabolome Annotation Workflow for untargeted tandem mass spectrometry."],"pmcid":["PMC9985203"],"funding_grant_id":["390713860","239748522-SFB 1127","239748522–SFB 1127"],"pubmed_authors":["Sorokina M","Peters K","Steinbeck C","Zulfiqar M","Gadelha L"],"additional_accession":[]},"is_claimable":false,"name":"MAW: the reproducible Metabolome Annotation Workflow for untargeted tandem mass spectrometry.","description":"Mapping the chemical space of compounds to chemical structures remains a challenge in metabolomics. Despite the advancements in untargeted liquid chromatography-mass spectrometry (LC-MS) to achieve a high-throughput profile of metabolites from complex biological resources, only a small fraction of these metabolites can be annotated with confidence. Many novel computational methods and tools have been developed to enable chemical structure annotation to known and unknown compounds such as in silico generated spectra and molecular networking. Here, we present an automated and reproducible Metabolome Annotation Workflow (MAW) for untargeted metabolomics data to further facilitate and automate the complex annotation by combining tandem mass spectrometry (MS<sup>2</sup>) input data pre-processi","dates":{"release":"2023-01-01T00:00:00Z","publication":"2023 Mar","modification":"2025-04-22T02:28:57.672Z","creation":"2025-02-18T23:45:04.599Z"},"accession":"S-EPMC9985203","cross_references":{"pubmed":["36871033"],"doi":["10.1186/s13321-023-00695-y"]}}