{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T04:03:13Z","timestamp":1782187393925,"version":"3.54.5"},"reference-count":56,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2022,3,25]],"date-time":"2022-03-25T00:00:00Z","timestamp":1648166400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/summer-heart-0930.chufeiyun1688.workers.dev:443\/https\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"name":"Scientific Research Project of Hunan Education Department","award":["19C1788"],"award-info":[{"award-number":["19C1788"]}]},{"name":"Foundation of Education Department of Liaoning Province","award":["LJKZ0280"],"award-info":[{"award-number":["LJKZ0280"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61902125"],"award-info":[{"award-number":["61902125"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,5,13]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Increasing evidences show that the occurrence of human complex diseases is closely related to microRNA (miRNA) variation and imbalance. For this reason, predicting disease-related miRNAs is essential for the diagnosis and treatment of complex human diseases. Although some current computational methods can effectively predict potential disease-related miRNAs, the accuracy of prediction should be further improved. In our study, a new computational method via deep forest ensemble learning based on autoencoder (DFELMDA) is proposed to predict miRNA\u2013disease associations. Specifically, a new feature representation strategy is proposed to obtain different types of feature representations (from miRNA and disease) for each miRNA\u2013disease association. Then, two types of low-dimensional feature representations are extracted by two deep autoencoders for predicting miRNA\u2013disease associations. Finally, two prediction scores of the miRNA\u2013disease associations are obtained by the deep random forest and combined to determine the final results. DFELMDA is compared with several classical methods on the The Human microRNA Disease Database (HMDD) dataset. Results reveal that the performance of this method is superior. The area under receiver operating characteristic curve (AUC) values obtained by DFELMDA through 5-fold and 10-fold cross-validation are 0.9552 and 0.9560, respectively. In addition, case studies on colon, breast and lung tumors of different disease types further demonstrate the excellent ability of DFELMDA to predict disease-associated miRNA\u2013disease. Performance analysis shows that DFELMDA can be used as an effective computational tool for predicting miRNA\u2013disease associations.<\/jats:p>","DOI":"10.1093\/bib\/bbac104","type":"journal-article","created":{"date-parts":[[2022,3,16]],"date-time":"2022-03-16T20:11:00Z","timestamp":1647461460000},"source":"Crossref","is-referenced-by-count":115,"title":["Identification of miRNA\u2013disease associations via deep forest ensemble learning based on autoencoder"],"prefix":"10.1093","volume":"23","author":[{"given":"Wei","family":"Liu","sequence":"first","affiliation":[{"name":"Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education, Xiangtan University, Xiangtan, 411105, China"},{"name":"School of Computer Science, Xiangtan University, Xiangtan, 411105, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hui","family":"Lin","sequence":"additional","affiliation":[{"name":"Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education, Xiangtan University, Xiangtan, 411105, China"},{"name":"School of Computer Science, Xiangtan University, Xiangtan, 411105, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Huang","sequence":"additional","affiliation":[{"name":"Academy of Arts and Design, Tsinghua University, Beijing, 10084, China"},{"name":"The Future Laboratory, Tsinghua University, Beijing, 10084, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Peng","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan, 411201, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ting","family":"Tang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education, Xiangtan University, Xiangtan, 411105, China"},{"name":"School of Computer Science, Xiangtan University, Xiangtan, 411105, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/summer-heart-0930.chufeiyun1688.workers.dev:443\/https\/orcid.org\/0000-0001-9713-1864","authenticated-orcid":false,"given":"Qi","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Computer Science and Software Engineering, University of Science and Technology Liaoning, Anshan, 114051, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/summer-heart-0930.chufeiyun1688.workers.dev:443\/https\/orcid.org\/0000-0001-8614-4555","authenticated-orcid":false,"given":"Li","family":"Yang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education, Xiangtan University, Xiangtan, 411105, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2022,3,25]]},"reference":[{"issue":"6","key":"2022051813462273600_ref1","doi-asserted-by":"crossref","first-page":"673","DOI":"10.1016\/S0092-8674(03)00428-8","article-title":"MicroRNA pathways in flies and worms: growth, death, fat, stress, and timing","volume":"113","author":"Ambros","year":"2003","journal-title":"Cell"},{"issue":"5752","key":"2022051813462273600_ref2","doi-asserted-by":"crossref","first-page":"1288","DOI":"10.1126\/science.1121566","article-title":"Encountering microRNAs in cell fate signaling","volume":"310","author":"Karp","year":"2005","journal-title":"Science"},{"issue":"5","key":"2022051813462273600_ref3","doi-asserted-by":"crossref","first-page":"563","DOI":"10.1016\/j.gde.2005.08.005","article-title":"How microRNAs control cell division, differentiation and death","volume":"15","author":"Miska","year":"2005","journal-title":"Curr Opin Genet Dev"},{"issue":"33","key":"2022051813462273600_ref4","doi-asserted-by":"crossref","first-page":"12481","DOI":"10.1073\/pnas.0605298103","article-title":"NF-kappaB-dependent induction of microRNA miR-146, an inhibitor targeted to signaling proteins of innate immune responses","volume":"103","author":"Taganov","year":"2006","journal-title":"Proc Natl Acad Sci U S A"},{"issue":"2","key":"2022051813462273600_ref5","doi-asserted-by":"crossref","first-page":"647","DOI":"10.1053\/j.gastro.2007.05.022","article-title":"MicroRNA-21 regulates expression of the PTEN tumor suppressor gene in human hepatocellular cancer","volume":"133","author":"Meng","year":"2007","journal-title":"Gastroenterology"},{"key":"2022051813462273600_ref6","doi-asserted-by":"crossref","first-page":"168","DOI":"10.1007\/s12539-021-00478-9","article-title":"Inferring gene regulatory networks using the improved Markov blanket discovery algorithm","volume":"14","author":"Liu","year":"2021","journal-title":"Interdiscip Sci"},{"issue":"5740","key":"2022051813462273600_ref7","doi-asserted-by":"crossref","first-page":"1577","DOI":"10.1126\/science.1113329","article-title":"Modulation of hepatitis C virus RNA abundance by a liver-specific MicroRNA","volume":"309","author":"Jopling","year":"2005","journal-title":"Science"},{"issue":"5858","key":"2022051813462273600_ref8","doi-asserted-by":"crossref","first-page":"1931","DOI":"10.1126\/science.1149460","article-title":"Switching from repression to activation: microRNAs can up-regulate translation","volume":"318","author":"Vasudevan","year":"2007","journal-title":"Science"},{"issue":"2","key":"2022051813462273600_ref9","doi-asserted-by":"crossref","first-page":"515","DOI":"10.1093\/bib\/bbx130","article-title":"MicroRNAs and complex diseases: from experimental results to computational models","volume":"20","author":"Chen","year":"2019","journal-title":"Brief Bioinform"},{"issue":"1","key":"2022051813462273600_ref10","doi-asserted-by":"crossref","first-page":"485","DOI":"10.1093\/bib\/bbz159","article-title":"NCMCMDA: miRNA-disease association prediction through neighborhood constraint matrix completion","volume":"22","author":"Chen","year":"2021","journal-title":"Brief Bioinform"},{"issue":"3","key":"2022051813462273600_ref11","doi-asserted-by":"crossref","first-page":"e1006865","DOI":"10.1371\/journal.pcbi.1006865","article-title":"LMTRDA: using logistic model tree to predict MiRNA-disease associations by fusing multi-source information of sequences and similarities","volume":"15","author":"Wang","year":"2019","journal-title":"PLoS Comput Biol"},{"issue":"6","key":"2022051813462273600_ref12","doi-asserted-by":"crossref","first-page":"bbab302","DOI":"10.1093\/bib\/bbab302","article-title":"Identification of miRNA-disease associations via multiple information integration with Bayesian ranking","volume":"22","author":"Zhu","year":"2021","journal-title":"Brief Bioinform"},{"issue":"6","key":"2022051813462273600_ref13","first-page":"797","article-title":"HLPI-ensemble: prediction of human lncRNA-protein interactions based on ensemble strategy","volume":"15","author":"Hu","year":"2018","journal-title":"RNA Biol"},{"issue":"3","key":"2022051813462273600_ref14","doi-asserted-by":"crossref","first-page":"535","DOI":"10.1007\/s12539-021-00458-z","article-title":"Using network distance analysis to predict lncRNA-miRNA interactions","volume":"13","author":"Zhang","year":"2021","journal-title":"Interdiscip Sci"},{"issue":"6","key":"2022051813462273600_ref15","doi-asserted-by":"crossref","first-page":"bbab286","DOI":"10.1093\/bib\/bbab286","article-title":"Circular RNAs and complex diseases: from experimental results to computational models","volume":"22","author":"Wang","year":"2021","journal-title":"Brief Bioinform"},{"issue":"3","key":"2022051813462273600_ref16","doi-asserted-by":"crossref","first-page":"e1005455","DOI":"10.1371\/journal.pcbi.1005455","article-title":"PBMDA: a novel and effective path-based computational model for miRNA-disease association prediction","volume":"13","author":"You","year":"2017","journal-title":"PLoS Comput Biol"},{"issue":"7","key":"2022051813462273600_ref17","doi-asserted-by":"crossref","first-page":"e1007209","DOI":"10.1371\/journal.pcbi.1007209","article-title":"Ensemble of decision tree reveals potential miRNA-disease associations","volume":"15","author":"Chen","year":"2019","journal-title":"PLoS Comput Biol"},{"issue":"24","key":"2022051813462273600_ref18","doi-asserted-by":"crossref","first-page":"4256","DOI":"10.1093\/bioinformatics\/bty503","article-title":"Predicting miRNA-disease association based on inductive matrix completion","volume":"34","author":"Chen","year":"2018","journal-title":"Bioinformatics"},{"issue":"1","key":"2022051813462273600_ref19","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1038\/s41419-017-0003-x","article-title":"EGBMMDA: extreme gradient boosting machine for MiRNA-disease association prediction","volume":"9","author":"Chen","year":"2018","journal-title":"Cell Death Dis"},{"issue":"Suppl 1","key":"2022051813462273600_ref20","doi-asserted-by":"crossref","first-page":"S2","DOI":"10.1186\/1752-0509-4-S1-S2","article-title":"Prioritization of disease microRNAs through a human phenome-microRNAome network","volume":"4","author":"Jiang","year":"2010","journal-title":"BMC Syst Biol"},{"issue":"10","key":"2022051813462273600_ref21","doi-asserted-by":"crossref","first-page":"2792","DOI":"10.1039\/c2mb25180a","article-title":"RWRMDA: predicting novel human microRNA-disease associations","volume":"8","author":"Chen","year":"2012","journal-title":"Mol Biosyst"},{"issue":"14","key":"2022051813462273600_ref22","doi-asserted-by":"crossref","first-page":"2425","DOI":"10.1093\/bioinformatics\/bty112","article-title":"Prediction of potential disease-associated microRNAs using structural perturbation method","volume":"34","author":"Zeng","year":"2018","journal-title":"Bioinformatics"},{"issue":"40","key":"2022051813462273600_ref23","doi-asserted-by":"crossref","first-page":"65257","DOI":"10.18632\/oncotarget.11251","article-title":"HGIMDA: heterogeneous graph inference for miRNA-disease association prediction","volume":"7","author":"Chen","year":"2016","journal-title":"Oncotarget"},{"key":"2022051813462273600_ref24","doi-asserted-by":"crossref","first-page":"21106","DOI":"10.1038\/srep21106","article-title":"WBSMDA: within and between score for MiRNA-disease association prediction","volume":"6","author":"Chen","year":"2016","journal-title":"Sci Rep"},{"issue":"8","key":"2022051813462273600_ref25","doi-asserted-by":"crossref","first-page":"e1006418","DOI":"10.1371\/journal.pcbi.1006418","article-title":"MDHGI: matrix decomposition and heterogeneous graph inference for miRNA-disease association prediction","volume":"14","author":"Chen","year":"2018","journal-title":"PLoS Comput Biol"},{"issue":"18","key":"2022051813462273600_ref26","doi-asserted-by":"crossref","first-page":"3178","DOI":"10.1093\/bioinformatics\/bty333","article-title":"BNPMDA: bipartite network projection for MiRNA-disease association prediction","volume":"34","author":"Chen","year":"2018","journal-title":"Bioinformatics"},{"key":"2022051813462273600_ref27","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1016\/j.jbi.2018.05.005","article-title":"Predicting microRNA-disease associations using label propagation based on linear neighborhood similarity","volume":"82","author":"Li","year":"2018","journal-title":"J Biomed Inform"},{"issue":"10","key":"2022051813462273600_ref28","doi-asserted-by":"crossref","first-page":"1857","DOI":"10.1158\/1535-7163.MCT-11-0055","article-title":"Prioritizing candidate disease miRNAs by topological features in the miRNA target-dysregulated network: case study of prostate cancer","volume":"10","author":"Xu","year":"2011","journal-title":"Mol Cancer Ther"},{"issue":"1","key":"2022051813462273600_ref29","doi-asserted-by":"crossref","first-page":"5501","DOI":"10.1038\/srep05501","article-title":"Semi-supervised learning for potential human microRNA-disease associations inference","volume":"4","author":"Chen","year":"2015","journal-title":"Sci Rep"},{"issue":"12","key":"2022051813462273600_ref30","doi-asserted-by":"crossref","first-page":"e1005912","DOI":"10.1371\/journal.pcbi.1005912","article-title":"LRSSLMDA: Laplacian regularized sparse subspace learning for MiRNA-disease association prediction","volume":"13","author":"Chen","year":"2017","journal-title":"PLoS Comput Biol"},{"issue":"22","key":"2022051813462273600_ref31","doi-asserted-by":"crossref","first-page":"4730","DOI":"10.1093\/bioinformatics\/btz297","article-title":"Adaptive boosting-based computational model for predicting potential miRNA-disease associations","volume":"35","author":"Zhao","year":"2019","journal-title":"Bioinformatics"},{"issue":"1","key":"2022051813462273600_ref32","doi-asserted-by":"crossref","first-page":"13877","DOI":"10.1038\/srep13877","article-title":"RBMMMDA: predicting multiple types of disease-microRNA associations","volume":"5","author":"Chen","year":"2015","journal-title":"Sci Rep"},{"issue":"3","key":"2022051813462273600_ref33","doi-asserted-by":"crossref","first-page":"bbaa186","DOI":"10.1093\/bib\/bbaa186","article-title":"Deep-belief network for predicting potential miRNA-disease associations","volume":"22","author":"Chen","year":"2021","journal-title":"Brief Bioinform"},{"issue":"21","key":"2022051813462273600_ref34","doi-asserted-by":"crossref","first-page":"4364","DOI":"10.1093\/bioinformatics\/btz254","article-title":"A learning-based framework for miRNA-disease association identification using neural networks","volume":"35","author":"Peng","year":"2019","journal-title":"Bioinformatics"},{"issue":"D1","key":"2022051813462273600_ref35","doi-asserted-by":"crossref","first-page":"D1070","DOI":"10.1093\/nar\/gkt1023","article-title":"HMDD v2.0: a database for experimentally supported human microRNA and disease associations","volume":"42","author":"Li","year":"2014","journal-title":"Nucleic Acid Res"},{"issue":"13","key":"2022051813462273600_ref36","doi-asserted-by":"crossref","first-page":"1644","DOI":"10.1093\/bioinformatics\/btq241","article-title":"Inferring the human microRNA functional similarity and functional network based on microRNA-associated diseases","volume":"26","author":"Wang","year":"2010","journal-title":"Bioinformatics"},{"issue":"D1","key":"2022051813462273600_ref37","doi-asserted-by":"crossref","first-page":"D940","DOI":"10.1093\/nar\/gkr972","article-title":"Disease ontology: a backbone for disease semantic integration","volume":"40","author":"Schriml","year":"2012","journal-title":"Nucleic Acid Res"},{"issue":"21","key":"2022051813462273600_ref38","doi-asserted-by":"crossref","first-page":"3036","DOI":"10.1093\/bioinformatics\/btr500","article-title":"Gaussian interaction profile kernels for predicting drug-target interaction","volume":"27","author":"Laarhoven","year":"2011","journal-title":"Bioinformatics"},{"issue":"20","key":"2022051813462273600_ref39","doi-asserted-by":"crossref","first-page":"2617","DOI":"10.1093\/bioinformatics\/btt426","article-title":"Novel human lncRNA-disease association inference based on lncRNA expression profiles","volume":"29","author":"Chen","year":"2013","journal-title":"Bioinformatics"},{"key":"2022051813462273600_ref40","doi-asserted-by":"crossref","first-page":"145040","DOI":"10.1016\/j.gene.2020.145040","article-title":"An ensemble approach for CircRNA-disease association prediction based on auto-encoder and deep neural network","volume":"762","author":"Deepthi","year":"2020","journal-title":"Gene"},{"issue":"1","key":"2022051813462273600_ref41","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forest","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach Learn"},{"issue":"4","key":"2022051813462273600_ref42","doi-asserted-by":"crossref","first-page":"1040","DOI":"10.1016\/j.jmb.2009.02.023","article-title":"Identification of DNA-binding proteins using structural, electrostatic and evolutionary features","volume":"387","author":"Nimrod","year":"2009","journal-title":"J Mol Biol"},{"issue":"1","key":"2022051813462273600_ref43","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1186\/1471-2156-7-23","article-title":"The challenge for genetic epidemiologists: how to analyze large numbers of SNPs in relation to complex diseases","volume":"7","author":"Heidema","year":"2006","journal-title":"BMC Genet"},{"issue":"1","key":"2022051813462273600_ref44","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1504\/IJDMB.2015.070852","article-title":"A novel random forests-based feature selection method for microarray expression data analysis","volume":"13","author":"Yao","year":"2015","journal-title":"Int J Data Min Bioinform"},{"issue":"24","key":"2022051813462273600_ref45","doi-asserted-by":"crossref","first-page":"3897","DOI":"10.1093\/bioinformatics\/btv480","article-title":"LncRNA-ID: long non-coding RNA IDentification using balanced random forests","volume":"31","author":"Achawanantakun","year":"2015","journal-title":"Bioinformatics"},{"issue":"1","key":"2022051813462273600_ref46","doi-asserted-by":"crossref","first-page":"17901","DOI":"10.1038\/s41598-020-75005-9","article-title":"Seq-SymRF: a random forest model predicts potential miRNA-disease associations based on information of sequences and clinical symptoms","volume":"10","author":"Li","year":"2020","journal-title":"Sci Rep"},{"issue":"4","key":"2022051813462273600_ref47","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1007\/s13312-011-0055-4","article-title":"Receiver operating characteristic (ROC) curve for medical researchers","volume":"48","author":"Kumar","year":"2011","journal-title":"Indian Pediatr"},{"issue":"7","key":"2022051813462273600_ref48","doi-asserted-by":"crossref","first-page":"1145","DOI":"10.1016\/S0031-3203(96)00142-2","article-title":"The use of the area under the ROC curve in the evaluation of machine learning algorithms","volume":"30","author":"Bradley","year":"1997","journal-title":"Pattern Recogn"},{"key":"2022051813462273600_ref49","doi-asserted-by":"crossref","first-page":"1316","DOI":"10.3389\/fgene.2019.01316","article-title":"Three-layer heterogeneous network combined with unbalanced random walk for miRNA-disease association prediction","volume":"10","author":"Yu","year":"2020","journal-title":"Front Genet"},{"key":"2022051813462273600_ref50","doi-asserted-by":"crossref","first-page":"40","DOI":"10.3389\/fbioe.2020.00040","article-title":"A computational study of potential miRNA-disease association inference based on ensemble learning and kernel ridge regression","volume":"8","author":"Peng","year":"2020","journal-title":"Front Bioeng Biotechnol"},{"issue":"4","key":"2022051813462273600_ref51","doi-asserted-by":"crossref","first-page":"bbaa240","DOI":"10.1093\/bib\/bbaa240","article-title":"A graph auto-encoder model for miRNA-disease associations prediction","volume":"22","author":"Li","year":"2021","journal-title":"Brief Bioinform"},{"issue":"4","key":"2022051813462273600_ref52","doi-asserted-by":"crossref","first-page":"e92921","DOI":"10.1371\/journal.pone.0092921","article-title":"Circulating exosomal microRNAs as biomarkers of colon cancer","volume":"9","author":"Ogata-Kawata","year":"2014","journal-title":"PLoS One"},{"issue":"5","key":"2022051813462273600_ref53","doi-asserted-by":"crossref","first-page":"635","DOI":"10.1016\/j.cell.2005.01.014","article-title":"RAS is regulated by the let-7 microRNA family","volume":"120","author":"Johnson","year":"2005","journal-title":"Cell"},{"issue":"2","key":"2022051813462273600_ref54","doi-asserted-by":"crossref","first-page":"152","DOI":"10.2174\/1871520616666160502122724","article-title":"Breast cancer: current molecular therapeutic targets and new players","volume":"17","author":"Nagini","year":"2017","journal-title":"Anticancer Agent Med Chem"},{"issue":"3","key":"2022051813462273600_ref55","first-page":"210","article-title":"Overexpression of circulating miRNA-21 and miRNA-146a in plasma samples of breast cancer patients","volume":"50","author":"Kumar","year":"2013","journal-title":"Indian J Biochem Biophys"},{"issue":"11","key":"2022051813462273600_ref56","doi-asserted-by":"crossref","first-page":"1405","DOI":"10.3390\/cells8111405","article-title":"Predicting disease related microRNA based on similarity and topology","volume":"8","author":"Chen","year":"2019","journal-title":"Cell"}],"container-title":["Briefings in Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/summer-heart-0930.chufeiyun1688.workers.dev:443\/https\/academic.oup.com\/bib\/article-pdf\/23\/3\/bbac104\/43745461\/bbac104.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/summer-heart-0930.chufeiyun1688.workers.dev:443\/https\/academic.oup.com\/bib\/article-pdf\/23\/3\/bbac104\/43745461\/bbac104.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,18]],"date-time":"2023-11-18T22:39:25Z","timestamp":1700347165000},"score":1,"resource":{"primary":{"URL":"https:\/\/summer-heart-0930.chufeiyun1688.workers.dev:443\/https\/academic.oup.com\/bib\/article\/doi\/10.1093\/bib\/bbac104\/6553934"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3,25]]},"references-count":56,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2022,5,13]]}},"URL":"https:\/\/summer-heart-0930.chufeiyun1688.workers.dev:443\/https\/doi.org\/10.1093\/bib\/bbac104","relation":{},"ISSN":["1467-5463","1477-4054"],"issn-type":[{"value":"1467-5463","type":"print"},{"value":"1477-4054","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2022,5]]},"published":{"date-parts":[[2022,3,25]]},"article-number":"bbac104"}}