{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Gaudry A"],"funding":["Ministerie van Buitenlandse Zaken","Schweizerischer Nationalfonds zur F??rderung der Wissenschaftlichen Forschung","Swiss National Science Foundation","Government of the United Kingdom","Swiss Open Research Data Grants","Bundesministerium f??r Bildung und Forschung"],"pagination":["494-510"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC10979503"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["10(3)"],"pubmed_abstract":["The ENPKG framework organizes large heterogeneous metabolomics data sets as a knowledge graph, offering exciting opportunities for drug discovery and chemodiversity characterization."],"journal":["ACS central science"],"pubmed_title":["A Sample-Centric and Knowledge-Driven Computational Framework for Natural Products Drug Discovery."],"pmcid":["PMC10979503"],"funding_grant_id":["164095","CRSII5_189921/1","316030","189921"],"pubmed_authors":["Mehl F","Ioset JR","Quiros-Guerrero LM","Pagni M","Queiroz EF","Cappelletti L","David B","Allard PM","Moretti S","Wolfender JL","Gaudry A","Grondin A","Marcourt L","Rutz A","Kaiser M"],"additional_accession":[]},"is_claimable":false,"name":"A Sample-Centric and Knowledge-Driven Computational Framework for Natural Products Drug Discovery.","description":"The ENPKG framework organizes large heterogeneous metabolomics data sets as a knowledge graph, offering exciting opportunities for drug discovery and chemodiversity characterization.","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Mar","modification":"2026-05-29T12:03:18.035Z","creation":"2025-04-06T07:46:37.76Z"},"accession":"S-EPMC10979503","cross_references":{"pubmed":["38559298"],"doi":["10.1021/acscentsci.3c00800"]}}