{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T22:32:23Z","timestamp":1773873143342,"version":"3.50.1"},"reference-count":66,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2022,6,20]],"date-time":"2022-06-20T00:00:00Z","timestamp":1655683200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000925","name":"National Health and Medical Research Council","doi-asserted-by":"publisher","award":["GNT1174405"],"award-info":[{"award-number":["GNT1174405"]}],"id":[{"id":"10.13039\/501100000925","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002322","name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100002322","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004901","name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de Minas Gerais","doi-asserted-by":"publisher","award":["MR\/M026302\/1"],"award-info":[{"award-number":["MR\/M026302\/1"]}],"id":[{"id":"10.13039\/501100004901","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,7,18]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>The rate of biological data generation has increased dramatically in recent years, which has driven the importance of databases as a resource to guide innovation and the generation of biological insights. Given the complexity and scale of these databases, automatic data classification is often required. Biological data sets are often hierarchical in nature, with varying degrees of complexity, imposing different challenges to train, test and validate accurate and generalizable classification models. While some approaches to classify hierarchical data have been proposed, no guidelines regarding their utility, applicability and limitations have been explored or implemented. These include \u2018Local\u2019 approaches considering the hierarchy, building models per level or node, and \u2018Global\u2019 hierarchical classification, using a flat classification approach. To fill this gap, here we have systematically contrasted the performance of \u2018Local per Level\u2019 and \u2018Local per Node\u2019 approaches with a \u2018Global\u2019 approach applied to two different hierarchical datasets: BioLip and CATH. The results show how different components of hierarchical data sets, such as variation coefficient and prediction by depth, can guide the choice of appropriate classification schemes. Finally, we provide guidelines to support this process when embarking on a hierarchical classification task, which will help optimize computational resources and predictive performance.<\/jats:p>","DOI":"10.1093\/bib\/bbac216","type":"journal-article","created":{"date-parts":[[2022,5,11]],"date-time":"2022-05-11T11:42:13Z","timestamp":1652269333000},"source":"Crossref","is-referenced-by-count":19,"title":["Evaluating hierarchical machine learning approaches to classify biological databases"],"prefix":"10.1093","volume":"23","author":[{"given":"P\u00e2mela M","family":"Rezende","sequence":"first","affiliation":[{"name":"Universidade Federal de Minas Gerais"},{"name":"Instituto Ren\u00e9 Rachou, Funda\u00e7\u00e3o Oswaldo Cruz"},{"name":"Stilingue Intelig\u00eancia Artificial"}]},{"given":"Joicymara S","family":"Xavier","sequence":"additional","affiliation":[{"name":"Universidade Federal de Minas Gerais"},{"name":"Instituto Ren\u00e9 Rachou, Funda\u00e7\u00e3o Oswaldo Cruz"},{"name":"Institute of Agricultural Sciences, Universidade Federal dos Vales do Jequitinhonha e Mucuri"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2948-2413","authenticated-orcid":false,"given":"David B","family":"Ascher","sequence":"additional","affiliation":[{"name":"School of Chemistry and Molecular Biosciences, University of Queensland"},{"name":"Systems and Computational Biology, Bio 21 Institute, University of Melbourne"},{"name":"Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute"}]},{"given":"Gabriel R","family":"Fernandes","sequence":"additional","affiliation":[{"name":"Instituto Ren\u00e9 Rachou, Funda\u00e7\u00e3o Oswaldo Cruz"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3004-2119","authenticated-orcid":false,"given":"Douglas E V","family":"Pires","sequence":"additional","affiliation":[{"name":"Systems and Computational Biology, Bio 21 Institute, University of Melbourne"},{"name":"Computational Biology and Clinical Informatics, Baker 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