{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,20]],"date-time":"2026-05-20T15:34:07Z","timestamp":1779291247053,"version":"3.51.4"},"reference-count":31,"publisher":"Oxford University Press (OUP)","issue":"16","license":[{"start":{"date-parts":[[2022,6,28]],"date-time":"2022-06-28T00:00:00Z","timestamp":1656374400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"Natural Sciences and Engineering Research Council (NSERC) and the Fonds de recherche du Qu\u00e9bec\u2014Nature et technologies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,8,10]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Motivation<\/jats:title><jats:p>Precise identification of Biosynthetic Gene Clusters (BGCs) is a challenging task. Performance of BGC discovery tools is limited by their capacity to accurately predict components belonging to candidate BGCs, often overestimating cluster boundaries. To support optimizing the composition and boundaries of candidate BGCs, we propose reinforcement learning approach relying on protein domains and functional annotations from expert curated BGCs.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The proposed reinforcement learning method aims to improve candidate BGCs obtained with state-of-the-art tools. It was evaluated on candidate BGCs obtained for two fungal genomes, Aspergillus niger and Aspergillus nidulans. The results highlight an improvement of the gene precision by above 15% for TOUCAN, fungiSMASH and DeepBGC; and cluster precision by above 25% for fungiSMASH and DeepBCG, allowing these tools to obtain almost perfect precision in cluster prediction. This can pave the way of optimizing current prediction of candidate BGCs in fungi, while minimizing the curation effort required by domain experts.<\/jats:p><\/jats:sec><jats:sec><jats:title>Availability and implementation<\/jats:title><jats:p>https:\/\/github.com\/bioinfoUQAM\/RL-bgc-components.<\/jats:p><\/jats:sec><jats:sec><jats:title>Supplementary information<\/jats:title><jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bioinformatics\/btac420","type":"journal-article","created":{"date-parts":[[2022,6,28]],"date-time":"2022-06-28T17:33:14Z","timestamp":1656437594000},"page":"3984-3991","source":"Crossref","is-referenced-by-count":12,"title":["Improving candidate Biosynthetic Gene Clusters in fungi through reinforcement learning"],"prefix":"10.1093","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3149-4547","authenticated-orcid":false,"given":"Hayda","family":"Almeida","sequence":"first","affiliation":[{"name":"Departement d\u2019Informatique, UQAM , Montr\u00e9al, QC H2X 3Y7, Canada"},{"name":"Centre for Structural and Functional Genomics, Concordia University , Montr\u00e9al, QC H4B 1R6, Canada"},{"name":"Laboratoire d\u2019Alg\u00e8bre, de Combinatoire, et d\u2019Informatique Math\u00e9matique (LACIM), UQAM , Montr\u00e9al, QC H2X 3Y, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Adrian","family":"Tsang","sequence":"additional","affiliation":[{"name":"Departement d\u2019Informatique, UQAM , Montr\u00e9al, QC H2X 3Y7, Canada"},{"name":"Centre for Structural and Functional Genomics, Concordia University , Montr\u00e9al, QC H4B 1R6, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abdoulaye Banir\u00e9","family":"Diallo","sequence":"additional","affiliation":[{"name":"Departement d\u2019Informatique, UQAM , Montr\u00e9al, QC H2X 3Y7, Canada"},{"name":"Laboratoire d\u2019Alg\u00e8bre, de Combinatoire, et d\u2019Informatique Math\u00e9matique (LACIM), UQAM , Montr\u00e9al, QC H2X 3Y, Canada"},{"name":"Centre of Excellence in Research on Orphan Diseases\u2014Courtois Foundation (CERMO-FC) , UQAM, Montr\u00e9al, QC H2X 3Y7, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2022,6,28]]},"reference":[{"key":"2023041408454861900_","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1016\/j.simyco.2018.10.001","article-title":"The gold-standard genome of Aspergillus niger NRRL 3 enables a detailed view of the diversity of sugar catabolism in fungi","volume":"91","author":"Aguilar-Pontes","year":"2018","journal-title":"Stud. Mycol"},{"key":"2023041408454861900_","first-page":"1280","author":"Almeida","year":"2019"},{"key":"2023041408454861900_","doi-asserted-by":"crossref","first-page":"lqaa098","DOI":"10.1093\/nargab\/lqaa098","article-title":"TOUCAN: a framework for fungal biosynthetic gene cluster discovery","volume":"2","author":"Almeida","year":"2020","journal-title":"NAR Genom. Bioinform"},{"key":"2023041408454861900_","author":"Angermueller","year":"2020"},{"key":"2023041408454861900_","doi-asserted-by":"crossref","first-page":"W29","DOI":"10.1093\/nar\/gkab335","article-title":"antiSMASH 6.0: improving cluster detection and comparison capabilities","volume":"49","author":"Blin","year":"2021","journal-title":"Nucleic Acids Res"},{"key":"2023041408454861900_","doi-asserted-by":"crossref","first-page":"1022","DOI":"10.1093\/bib\/bbx020","article-title":"Bioinformatics tools for the identification of gene clusters that biosynthesize specialized metabolites","volume":"19","author":"Chavali","year":"2018","journal-title":"Brief. Bioinform"},{"key":"2023041408454861900_","doi-asserted-by":"crossref","first-page":"412","DOI":"10.1016\/j.cell.2014.06.034","article-title":"Insights into secondary metabolism from a global analysis of prokaryotic biosynthetic gene clusters","volume":"158","author":"Cimermancic","year":"2014","journal-title":"Cell"},{"key":"2023041408454861900_","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1186\/s13059-017-1151-0","article-title":"Comparative genomics reveals high biological diversity and specific adaptations in the industrially and medically important fungal genus Aspergillus","volume":"18","author":"de Vries","year":"2017","journal-title":"Genome Biol"},{"key":"2023041408454861900_","doi-asserted-by":"crossref","first-page":"e00153-20","DOI":"10.1128\/mSphere.00156-20","article-title":"Diversity of secondary metabolism in Aspergillus nidulans clinical isolates","volume":"5","author":"Drott","year":"2020","journal-title":"mSphere"},{"key":"2023041408454861900_","doi-asserted-by":"crossref","first-page":"D427","DOI":"10.1093\/nar\/gky995","article-title":"The Pfam protein families database in 2019","volume":"47","author":"El-Gebali","year":"2019","journal-title":"Nucleic Acids Res"},{"key":"2023041408454861900_","doi-asserted-by":"crossref","first-page":"374","DOI":"10.3390\/jof7050374","article-title":"Identification of a novel biosynthetic gene cluster in Aspergillus niger using comparative genomics","volume":"7","author":"Evdokias","year":"2021","journal-title":"JoF"},{"key":"2023041408454861900_","first-page":"3668","author":"Gottipati","year":"2020"},{"key":"2023041408454861900_","doi-asserted-by":"crossref","first-page":"e110","DOI":"10.1093\/nar\/gkz654","article-title":"A deep learning genome-mining strategy for biosynthetic gene cluster prediction","volume":"47","author":"Hannigan","year":"2019","journal-title":"Nucleic Acids Res"},{"key":"2023041408454861900_","doi-asserted-by":"crossref","first-page":"1250","DOI":"10.1109\/TCBB.2018.2830357","article-title":"Control of gene regulatory networks using Bayesian inverse reinforcement learning","volume":"16","author":"Imani","year":"2019","journal-title":"IEEE\/ACM Trans. Comput. Biol. Bioinform"},{"key":"2023041408454861900_","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1186\/1471-2180-13-91","article-title":"Comprehensive annotation of secondary metabolite biosynthetic genes and gene clusters of Aspergillus nidulans, A. fumigatus, A. niger and A. oryzae","volume":"13","author":"Inglis","year":"2013","journal-title":"BMC Microbiol"},{"key":"2023041408454861900_","first-page":"D454","article-title":"MIBiG 2.0: a repository for biosynthetic gene clusters of known function","volume":"48","author":"Kautsar","year":"2020","journal-title":"Nucleic Acids Res"},{"key":"2023041408454861900_","doi-asserted-by":"crossref","first-page":"671","DOI":"10.1038\/nchembio.1897","article-title":"Translating biosynthetic gene clusters into fungal armor and weaponry","volume":"11","author":"Keller","year":"2015","journal-title":"Nat. Chem. Biol"},{"key":"2023041408454861900_","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1038\/s41579-018-0121-1","article-title":"Fungal secondary metabolism: regulation, function and drug discovery","volume":"17","author":"Keller","year":"2019","journal-title":"Nat. Rev. Microbiol"},{"key":"2023041408454861900_","doi-asserted-by":"crossref","first-page":"736","DOI":"10.1016\/j.fgb.2010.06.003","article-title":"SMURF: genomic mapping of fungal secondary metabolite clusters","volume":"47","author":"Khaldi","year":"2010","journal-title":"Fungal Genet. Biol"},{"key":"2023041408454861900_","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1016\/j.fgb.2019.06.001","article-title":"Strategies to establish the link between biosynthetic gene clusters and secondary metabolites","volume":"130","author":"Kj\u00e6rb\u00f8lling","year":"2019","journal-title":"Fungal Genet. Biol"},{"key":"2023041408454861900_","doi-asserted-by":"crossref","first-page":"1106","DOI":"10.1038\/s41467-019-14051-y","article-title":"A comparative genomics study of 23 Aspergillus species from section Flavi","volume":"11","author":"Kj\u00e6rb\u00f8lling","year":"2020","journal-title":"Nat. Commun"},{"key":"2023041408454861900_","doi-asserted-by":"crossref","first-page":"D807","DOI":"10.1093\/nar\/gky1053","article-title":"OrthoDB v10: sampling the diversity of animal, plant, fungal, protist, bacterial and viral genomes for evolutionary and functional annotations of orthologs","volume":"47","author":"Kriventseva","year":"2019","journal-title":"Nucleic Acids Res"},{"key":"2023041408454861900_","doi-asserted-by":"crossref","first-page":"2063","DOI":"10.1109\/TNNLS.2018.2790388","article-title":"Applications of deep learning and reinforcement learning to biological data","volume":"29","author":"Mahmud","year":"2018","journal-title":"IEEE Trans. Neural Netw. Learn. Syst"},{"key":"2023041408454861900_","first-page":"54","volume-title":"Proceedings of the 7th International Workshop Soft Computing Applications (SOFA 2016), Arad, Romania, August 24\u201326, 2016","author":"Mircea","year":"2018"},{"key":"2023041408454861900_","doi-asserted-by":"crossref","first-page":"8953","DOI":"10.1073\/pnas.1507606112","article-title":"Yeast homologous recombination-based promoter engineering for the activation of silent natural product biosynthetic gene clusters","volume":"112","author":"Montiel","year":"2015","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"2023041408454861900_","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1038\/s42256-019-0025-4","article-title":"Reinforcement learning in artificial and biological systems","volume":"1","author":"Neftci","year":"2019","journal-title":"Nat. Mach. Intell"},{"key":"2023041408454861900_","volume-title":"Reinforcement Learning: An Introduction","author":"Sutton","year":"2018"},{"key":"2023041408454861900_","doi-asserted-by":"crossref","first-page":"447","DOI":"10.1093\/dnares\/dsu010","article-title":"Motif-independent prediction of a secondary metabolism gene cluster using comparative genomics: application to sequenced genomes of Aspergillus and ten other filamentous fungal species","volume":"21","author":"Takeda","year":"2014","journal-title":"DNA Res"},{"key":"2023041408454861900_","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1007\/BF00992698","article-title":"Q-learning","volume":"8","author":"Watkins","year":"1992","journal-title":"Mach. Learn"},{"key":"2023041408454861900_","doi-asserted-by":"crossref","first-page":"1138","DOI":"10.1093\/bioinformatics\/btv713","article-title":"CASSIS and SMIPS: promoter-based prediction of secondary metabolite gene clusters in eukaryotic genomes","volume":"32","author":"Wolf","year":"2016","journal-title":"Bioinformatics"},{"key":"2023041408454861900_","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.mib.2019.03.003","article-title":"Unlocking the trove of metabolic treasures: activating silent biosynthetic gene clusters in bacteria and fungi","volume":"51","author":"Zhang","year":"2019","journal-title":"Curr. Opin. Microbiol"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btac420\/44834214\/btac420.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/38\/16\/3984\/49889902\/btac420.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/38\/16\/3984\/49889902\/btac420.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,23]],"date-time":"2023-11-23T21:16:44Z","timestamp":1700774204000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/38\/16\/3984\/6619162"}},"subtitle":[],"editor":[{"given":"Zhiyong","family":"Lu","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2022,6,28]]},"references-count":31,"journal-issue":{"issue":"16","published-print":{"date-parts":[[2022,8,10]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btac420","relation":{},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"value":"1367-4803","type":"print"},{"value":"1367-4811","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2022,8,15]]},"published":{"date-parts":[[2022,6,28]]}}}