{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Sher D"],"funding":["Simons Foundation Postdoctoral Fellowship in Marine Microbial Ecology","Israel Science Foundation","Data Science Research Center, University of Haifa"],"pagination":["e0321141"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12021255"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["20(4)"],"pubmed_abstract":["Inferring the metabolic capabilities of an organism from its genome is a challenging process, relying on computationally-derived or manually curated metabolic networks. Manual curation can correct mistakes in the draft network and add missing reactions based on the literature, but requires significant expertise and is often the bottleneck for high-quality metabolic reconstructions. Here, we present a synopsis of a community curation workshop for the model marine bacterium Alteromonas macleodii ATCC 27126 and its genome database in BioCyc, focusing on pathways for utilizing organic carbon and nitrogen sources. Due to the scarcity of biochemical information or gene knock-outs, the curation process relied primarily on published growth phenotypes and bioinformatic analyses, including compariso"],"journal":["PloS one"],"pubmed_title":["Collaborative metabolic curation of an emerging model marine bacterium, Alteromonas macleodii ATCC 27126."],"pmcid":["PMC12021255"],"funding_grant_id":["993200","1786/20"],"pubmed_authors":["Liddor Naim M","Gifford S","Karp P","George EE","Moore LR","Sher D","Koedooder C","Shrivastava V","Mireles R","Valiya Kalladi WB","Soussan-Farhat Y","Weissberg O","Wietz M","Itelson L","Malavin S","Sade D","Idan T","Abu Hamoud A","Zoccarato L","Barak N","Barreto Filho MM"],"additional_accession":[]},"is_claimable":false,"name":"Collaborative metabolic curation of an emerging model marine bacterium, Alteromonas macleodii ATCC 27126.","description":"Inferring the metabolic capabilities of an organism from its genome is a challenging process, relying on computationally-derived or manually curated metabolic networks. Manual curation can correct mistakes in the draft network and add missing reactions based on the literature, but requires significant expertise and is often the bottleneck for high-quality metabolic reconstructions. Here, we present a synopsis of a community curation workshop for the model marine bacterium Alteromonas macleodii ATCC 27126 and its genome database in BioCyc, focusing on pathways for utilizing organic carbon and nitrogen sources. Due to the scarcity of biochemical information or gene knock-outs, the curation process relied primarily on published growth phenotypes and bioinformatic analyses, including compariso","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025","modification":"2026-04-08T19:49:21.108Z","creation":"2025-07-01T03:05:05.126Z"},"accession":"S-EPMC12021255","cross_references":{"pubmed":["40273159"],"doi":["10.1371/journal.pone.0321141"]}}