{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,11]],"date-time":"2026-05-11T05:59:58Z","timestamp":1778479198175,"version":"3.51.4"},"reference-count":63,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2022,1,29]],"date-time":"2022-01-29T00:00:00Z","timestamp":1643414400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["32071465"],"award-info":[{"award-number":["32071465"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["31871334"],"award-info":[{"award-number":["31871334"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["31671374"],"award-info":[{"award-number":["31671374"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program","doi-asserted-by":"publisher","award":["2018YFC0910502"],"award-info":[{"award-number":["2018YFC0910502"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,3,10]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>With the rapid accumulation of microbiome data around the world, numerous computational bioinformatics methods have been developed for pattern mining from such paramount microbiome data. Current microbiome data mining methods, such as gene and species mining, rely heavily on sequence comparison. Most of these methods, however, have a clear trade-off, particularly, when it comes to big-data analytical efficiency and accuracy. Microbiome entities are usually organized in ontology structures, and pattern mining methods that have considered ontology structures could offer advantages in mining efficiency and accuracy. Here, we have summarized the ontology-aware neural network (ONN) as a novel framework for microbiome data mining. We have discussed the applications of ONN in multiple contexts, including gene mining, species mining and microbial community dynamic pattern mining. We have then highlighted one of the most important characteristics of ONN, namely, novel knowledge discovery, which makes ONN a standout among all microbiome data mining methods. Finally, we have provided several applications to showcase the advantage of ONN over other methods in microbiome data mining. In summary, ONN represents a paradigm shift for pattern mining from microbiome data: from traditional machine learning approach to ontology-aware and model-based approach, which has found its broad application scenarios in microbiome data mining.<\/jats:p>","DOI":"10.1093\/bib\/bbac005","type":"journal-article","created":{"date-parts":[[2022,1,11]],"date-time":"2022-01-11T12:09:31Z","timestamp":1641902971000},"source":"Crossref","is-referenced-by-count":4,"title":["Ontology-aware neural network: a general framework for pattern mining from microbiome data"],"prefix":"10.1093","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3702-9416","authenticated-orcid":false,"given":"Yuguo","family":"Zha","sequence":"first","affiliation":[{"name":"Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Department of Bioinformatics and Systems Biology, Center of AI Biology, College of Life Science and Technology, Huazhong University of Science and Technology, 1037 Luoyu Road Wuhan, Hubei, Wuhan 430074, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3325-5387","authenticated-orcid":false,"given":"Kang","family":"Ning","sequence":"additional","affiliation":[{"name":"Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Department of Bioinformatics and Systems Biology, Center of AI Biology, College of Life Science and Technology, Huazhong University of Science and Technology, 1037 Luoyu Road Wuhan, Hubei, Wuhan 430074, China"}]}],"member":"286","published-online":{"date-parts":[[2022,1,29]]},"reference":[{"key":"2022031506322619700_ref1","doi-asserted-by":"crossref","first-page":"3491","DOI":"10.1093\/jac\/dkaa345","article-title":"ResFinder 4.0 for predictions of phenotypes from genotypes","volume":"75","author":"Bortolaia","year":"2020","journal-title":"J Antimicrob Chemother"},{"key":"2022031506322619700_ref2","doi-asserted-by":"crossref","first-page":"1789","DOI":"10.1093\/bioinformatics\/bty844","article-title":"Strain-GeMS: optimized subspecies identification from microbiome data based on accurate variant modeling","volume":"35","author":"Tan","year":"2019","journal-title":"Bioinformatics"},{"key":"2022031506322619700_ref3","doi-asserted-by":"crossref","first-page":"e67","DOI":"10.1093\/nar\/gku138","article-title":"Strain\/species identification in metagenomes using genome-specific markers","volume":"42","author":"Tu","year":"2014","journal-title":"Nucleic Acids Res"},{"key":"2022031506322619700_ref4","doi-asserted-by":"crossref","first-page":"2254","DOI":"10.1136\/gutjnl-2018-317298","article-title":"Resilience of human gut microbial communities for the long stay with multiple dietary shifts","volume":"68","author":"Liu","year":"2019","journal-title":"Gut"},{"key":"2022031506322619700_ref5","doi-asserted-by":"crossref","first-page":"761","DOI":"10.1038\/nmeth.1650","article-title":"Bayesian community-wide culture-independent microbial source tracking","volume":"8","author":"Knights","year":"2011","journal-title":"Nat Methods"},{"key":"2022031506322619700_ref6","doi-asserted-by":"crossref","first-page":"627","DOI":"10.1038\/s41592-019-0431-x","article-title":"FEAST: fast expectation-maximization for microbial source tracking","volume":"16","author":"Shenhav","year":"2019","journal-title":"Nat Methods"},{"key":"2022031506322619700_ref7","doi-asserted-by":"crossref","first-page":"D325","DOI":"10.1093\/nar\/gkaa1113","article-title":"The Gene Ontology resource: enriching a GOld mine","volume":"49","author":"The Gene Ontology Consortium","year":"2021","journal-title":"Nucleic Acids Res"},{"key":"2022031506322619700_ref8","first-page":"D517","article-title":"CARD 2020: antibiotic resistome surveillance with the comprehensive antibiotic resistance database","volume":"48","author":"Alcock","year":"2020","journal-title":"Nucleic Acids Res"},{"key":"2022031506322619700_ref9","doi-asserted-by":"crossref","first-page":"12764","DOI":"10.1073\/pnas.1423041112","article-title":"Synthesis of phylogeny and taxonomy into a comprehensive tree of life","volume":"112","author":"Hinchliff","year":"2015","journal-title":"Proc Natl Acad Sci U S A"},{"key":"2022031506322619700_ref10","doi-asserted-by":"crossref","first-page":"16048","DOI":"10.1038\/nmicrobiol.2016.48","article-title":"A new view of the tree of life","volume":"1","author":"Hug","year":"2016","journal-title":"Nat Microbiol"},{"key":"2022031506322619700_ref11","first-page":"D570","article-title":"MGnify: the microbiome analysis resource in 2020","volume":"48","author":"Mitchell","year":"2020","journal-title":"Nucleic Acids Res"},{"key":"2022031506322619700_ref12","doi-asserted-by":"crossref","first-page":"660","DOI":"10.1093\/bioinformatics\/btx624","article-title":"DeepGO: predicting protein functions from sequence and interactions using a deep ontology-aware classifier","volume":"34","author":"Kulmanov","year":"2018","journal-title":"Bioinformatics"},{"key":"2022031506322619700_ref13","article-title":"Ontology-aware deep learning enables novel antibiotic resistance gene discovery towards comprehensive profiling of ARGs","author":"Zha","year":"2021","journal-title":"bioRxiv"},{"key":"2022031506322619700_ref14","article-title":"Ontology-aware deep learning enables ultrafast, accurate and interpretable source tracking among sub-million microbial community samples from hundreds of niches","author":"Zha","year":"2020","journal-title":"bioRxiv"},{"key":"2022031506322619700_ref15","article-title":"Enabling technology for microbial source tracking based on transfer learning: from ontology-aware general knowledge to context-aware expert systems","author":"Chong","year":"2021","journal-title":"bioRxiv"},{"key":"2022031506322619700_ref16","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1186\/s40168-018-0401-z","article-title":"DeepARG: a deep learning approach for predicting antibiotic resistance genes from metagenomic data","volume":"6","author":"Arango-Argoty","year":"2018","journal-title":"Microbiome"},{"key":"2022031506322619700_ref17","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1186\/s40168-021-01002-3","article-title":"HMD-ARG: hierarchical multi-task deep learning for annotating antibiotic resistance genes","volume":"9","author":"Li","year":"2021","journal-title":"Microbiome"},{"key":"2022031506322619700_ref18","doi-asserted-by":"crossref","first-page":"3707","DOI":"10.1093\/bioinformatics\/btab482","article-title":"phyLoSTM: a novel deep learning model on disease prediction from longitudinal microbiome data","volume":"37","author":"Sharma","year":"2021","journal-title":"Bioinformatics"},{"key":"2022031506322619700_ref19","doi-asserted-by":"crossref","DOI":"10.1093\/bib\/bbab223","article-title":"Human host status inference from temporal microbiome changes via recurrent neural networks","volume":"22","author":"Chen","year":"2021","journal-title":"Brief Bioinform"},{"key":"2022031506322619700_ref20","doi-asserted-by":"crossref","first-page":"599","DOI":"10.1038\/d41586-019-01674-w","article-title":"What's next for the microbiome community?","volume":"569","author":"After the Integrative Human Microbiome Project","year":"2019","journal-title":"Nature"},{"key":"2022031506322619700_ref21","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1038\/s41586-019-1238-8","article-title":"The Integrative Human Microbiome Project","volume":"569","author":"Proctor","year":"2019","journal-title":"Nature"},{"key":"2022031506322619700_ref22","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1038\/nature24621","article-title":"A communal catalogue reveals Earth's multiscale microbial diversity","volume":"551","author":"Thompson","year":"2017","journal-title":"Nature"},{"key":"2022031506322619700_ref23","doi-asserted-by":"crossref","first-page":"1261359","DOI":"10.1126\/science.1261359","article-title":"Ocean plankton. Structure and function of the global ocean microbiome","volume":"348","author":"Sunagawa","year":"2015","journal-title":"Science"},{"key":"2022031506322619700_ref24","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1038\/nmeth.3176","article-title":"Fast and sensitive protein alignment using DIAMOND","volume":"12","author":"Buchfink","year":"2015","journal-title":"Nat Methods"},{"key":"2022031506322619700_ref25","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":"2022031506322619700_ref26","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":"2022031506322619700_ref27","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":"2022031506322619700_ref28","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1038\/nature06592","article-title":"An Earth-system perspective of the global nitrogen cycle","volume":"451","author":"Gruber","year":"2008","journal-title":"Nature"},{"key":"2022031506322619700_ref29","doi-asserted-by":"crossref","DOI":"10.1093\/femsec\/fiy175","article-title":"The role of wetland microorganisms in plant-litter decomposition and soil organic matter formation: a critical review","volume":"94","author":"Yarwood","year":"2018","journal-title":"FEMS Microbiol Ecol"},{"key":"2022031506322619700_ref30","doi-asserted-by":"crossref","first-page":"377","DOI":"10.1038\/s41591-019-0377-7","article-title":"The microbiome, cancer, and cancer therapy","volume":"25","author":"Helmink","year":"2019","journal-title":"Nat Med"},{"key":"2022031506322619700_ref31","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1016\/j.gpb.2018.02.004","article-title":"Stereotypes about enterotype: the old and new ideas","volume":"17","author":"Cheng","year":"2019","journal-title":"Genomics Proteomics Bioinformatics"},{"key":"2022031506322619700_ref32","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1038\/nature09944","article-title":"Enterotypes of the human gut microbiome","volume":"473","author":"Arumugam","year":"2011","journal-title":"Nature"},{"key":"2022031506322619700_ref33","doi-asserted-by":"crossref","first-page":"626","DOI":"10.1101\/gr.216242.116","article-title":"Microbial strain-level population structure and genetic diversity from metagenomes","volume":"27","author":"Truong","year":"2017","journal-title":"Genome Res"},{"key":"2022031506322619700_ref34","doi-asserted-by":"crossref","first-page":"1045","DOI":"10.1038\/nbt.3319","article-title":"ConStrains identifies microbial strains in metagenomic datasets","volume":"33","author":"Luo","year":"2015","journal-title":"Nat Biotechnol"},{"key":"2022031506322619700_ref35","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1126\/science.aad2646","article-title":"Microbial community assembly and metabolic function during mammalian corpse decomposition","volume":"351","author":"Metcalf Jessica","year":"2016","journal-title":"Science"},{"key":"2022031506322619700_ref36","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1016\/j.ymeth.2019.04.008","article-title":"Deep learning in bioinformatics: introduction, application, and perspective in the big data era","volume":"166","author":"Li","year":"2019","journal-title":"Methods"},{"key":"2022031506322619700_ref37","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1038\/nrg3920","article-title":"Machine learning applications in genetics and genomics","volume":"16","author":"Libbrecht","year":"2015","journal-title":"Nat Rev Genet"},{"key":"2022031506322619700_ref38","doi-asserted-by":"crossref","first-page":"214","DOI":"10.3389\/fgene.2019.00214","article-title":"Recent advances of deep learning in bioinformatics and computational biology","volume":"10","author":"Tang","year":"2019","journal-title":"Front Genet"},{"key":"2022031506322619700_ref39","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1038\/s41588-018-0295-5","article-title":"A primer on deep learning in genomics","volume":"51","author":"Zou","year":"2019","journal-title":"Nat Genet"},{"key":"2022031506322619700_ref40","doi-asserted-by":"crossref","first-page":"428","DOI":"10.1038\/s41579-020-0364-5","article-title":"Tara Oceans: towards global ocean ecosystems biology","volume":"18","author":"Sunagawa","year":"2020","journal-title":"Nat Rev Microbiol"},{"key":"2022031506322619700_ref41","doi-asserted-by":"crossref","first-page":"834","DOI":"10.1038\/nbt.2942","article-title":"An integrated catalog of reference genes in the human gut microbiome","volume":"32","author":"Li","year":"2014","journal-title":"Nat Biotechnol"},{"key":"2022031506322619700_ref42","doi-asserted-by":"crossref","first-page":"1552","DOI":"10.1038\/s41559-019-1005-0","article-title":"Hyperdiverse archaea near life limits at the polyextreme geothermal Dallol area","volume":"3","author":"Belilla","year":"2019","journal-title":"Nature Ecol Evol"},{"key":"2022031506322619700_ref43","doi-asserted-by":"crossref","DOI":"10.1016\/j.scitotenv.2020.138259","article-title":"Microbiome structure and function in rhizosphere of Jerusalem artichoke grown in saline land","volume":"724","author":"Yue","year":"2020","journal-title":"Sci Total Environ"},{"key":"2022031506322619700_ref44","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1186\/s40168-019-0623-8","article-title":"Archaea dominate the microbial community in an ecosystem with low-to-moderate temperature and extreme acidity","volume":"7","author":"Korzhenkov","year":"2019","journal-title":"Microbiome"},{"key":"2022031506322619700_ref45","doi-asserted-by":"crossref","first-page":"1344","DOI":"10.1111\/1462-2920.14568","article-title":"Diverse anaerobic methane- and multi-carbon alkane-metabolizing archaea coexist and show activity in Guaymas Basin hydrothermal sediment","volume":"21","author":"Wang","year":"2019","journal-title":"Environ Microbiol"},{"key":"2022031506322619700_ref46","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1038\/nrmicro.2016.177","article-title":"Virus taxonomy in the age of metagenomics","volume":"15","author":"Simmonds","year":"2017","journal-title":"Nat Rev Microbiol"},{"key":"2022031506322619700_ref47","article-title":"Protist 10,000 Genomes Project","volume":"1","author":"Miao","year":"2020","journal-title":"Innovation"},{"key":"2022031506322619700_ref48","doi-asserted-by":"crossref","first-page":"690","DOI":"10.1016\/j.chom.2015.04.004","article-title":"Dynamics and stabilization of the human gut microbiome during the first year of life","volume":"17","author":"B\u00e4ckhed","year":"2015","journal-title":"Cell Host Microbe"},{"key":"2022031506322619700_ref49","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1038\/nature11319","article-title":"Gut microbiota composition correlates with diet and health in the elderly","volume":"488","author":"Claesson","year":"2012","journal-title":"Nature"},{"key":"2022031506322619700_ref50","doi-asserted-by":"crossref","first-page":"559","DOI":"10.1038\/nature12820","article-title":"Diet rapidly and reproducibly alters the human gut microbiome","volume":"505","author":"David","year":"2014","journal-title":"Nature"},{"key":"2022031506322619700_ref51","doi-asserted-by":"crossref","first-page":"1237439","DOI":"10.1126\/science.1237439","article-title":"The long-term stability of the human gut microbiota","volume":"341","author":"Faith Jeremiah","year":"2013","journal-title":"Science"},{"key":"2022031506322619700_ref52","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1126\/science.1208344","article-title":"Linking long-term dietary patterns with gut microbial enterotypes","volume":"334","author":"Wu Gary","year":"2011","journal-title":"Science"},{"key":"2022031506322619700_ref53","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1038\/nature18846","article-title":"Diet\u2013microbiota interactions as moderators of human metabolism","volume":"535","author":"Sonnenburg","year":"2016","journal-title":"Nature"},{"key":"2022031506322619700_ref54","doi-asserted-by":"crossref","first-page":"907","DOI":"10.1016\/S2213-2600(18)30510-1","article-title":"Functional effects of the microbiota in chronic respiratory disease","volume":"7","author":"Budden","year":"2019","journal-title":"Lancet Respir Med"},{"key":"2022031506322619700_ref55","doi-asserted-by":"crossref","first-page":"573","DOI":"10.1038\/nrgastro.2017.88","article-title":"Gut microbiota and IBD: causation or correlation?","volume":"14","author":"Ni","year":"2017","journal-title":"Nat Rev Gastroenterol Hepatol"},{"key":"2022031506322619700_ref56","doi-asserted-by":"crossref","DOI":"10.1093\/bib\/bbaa158","article-title":"Microbes and complex diseases: from experimental results to computational models","volume":"22","author":"Zhao","year":"2021","journal-title":"Brief Bioinform"},{"key":"2022031506322619700_ref57","doi-asserted-by":"crossref","first-page":"4635","DOI":"10.1038\/s41467-020-18476-8","article-title":"A predictive index for health status using species-level gut microbiome profiling","volume":"11","author":"Gupta","year":"2020","journal-title":"Nat Commun"},{"key":"2022031506322619700_ref58","doi-asserted-by":"crossref","first-page":"1954","DOI":"10.1093\/bib\/bbz105","article-title":"Managing batch effects in microbiome data","volume":"21","author":"Wang","year":"2020","journal-title":"Brief Bioinform"},{"key":"2022031506322619700_ref59","doi-asserted-by":"crossref","first-page":"690","DOI":"10.1038\/nrg.2017.63","article-title":"Human genetic variation and the gut microbiome in disease","volume":"18","author":"Hall","year":"2017","journal-title":"Nat Rev Genet"},{"key":"2022031506322619700_ref60","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1016\/j.jaci.2019.11.003","article-title":"The microbiome and inflammatory bowel disease","volume":"145","author":"Glassner","year":"2020","journal-title":"J Allergy Clin Immunol"},{"key":"2022031506322619700_ref61","doi-asserted-by":"crossref","first-page":"e0007231","DOI":"10.1371\/journal.pntd.0007231","article-title":"A computational method for the identification of dengue, Zika and chikungunya virus species and genotypes","volume":"13","author":"Fonseca","year":"2019","journal-title":"PLoS Negl Trop Dis"},{"key":"2022031506322619700_ref62","doi-asserted-by":"crossref","first-page":"733","DOI":"10.1093\/bioinformatics\/btw715","article-title":"A novel approach based on KATZ measure to predict associations of human microbiota with non-infectious diseases","volume":"33","author":"Chen","year":"2017","journal-title":"Bioinformatics"},{"key":"2022031506322619700_ref63","doi-asserted-by":"crossref","first-page":"233","DOI":"10.3389\/fmicb.2017.00233","article-title":"PBHMDA: path-based human microbe-disease association prediction","volume":"8","author":"Huang","year":"2017","journal-title":"Front Microbiol"}],"container-title":["Briefings in Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/23\/2\/bbac005\/42806483\/bbac005.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/23\/2\/bbac005\/42806483\/bbac005.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,15]],"date-time":"2023-11-15T17:25:38Z","timestamp":1700069138000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bib\/article\/doi\/10.1093\/bib\/bbac005\/6517031"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,29]]},"references-count":63,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2022,3,10]]}},"URL":"https:\/\/doi.org\/10.1093\/bib\/bbac005","relation":{},"ISSN":["1467-5463","1477-4054"],"issn-type":[{"value":"1467-5463","type":"print"},{"value":"1477-4054","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2022,3]]},"published":{"date-parts":[[2022,1,29]]},"article-number":"bbac005"}}