{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,19]],"date-time":"2026-05-19T22:12:20Z","timestamp":1779228740600,"version":"3.51.4"},"reference-count":59,"publisher":"Oxford University Press (OUP)","issue":"15","license":[{"start":{"date-parts":[[2021,1,30]],"date-time":"2021-01-30T00:00:00Z","timestamp":1611964800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"name":"Jilin Provincial Key Laboratory of Big Data Intelligent Computing","award":["20180622002JC"],"award-info":[{"award-number":["20180622002JC"]}]},{"DOI":"10.13039\/501100010211","name":"Education Department of Jilin Province","doi-asserted-by":"publisher","award":["JJKH20180145KJ"],"award-info":[{"award-number":["JJKH20180145KJ"]}],"id":[{"id":"10.13039\/501100010211","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Bioknow MedAI Institute","award":["BMCPP-2018-001"],"award-info":[{"award-number":["BMCPP-2018-001"]}]},{"name":"Fundamental Research Funds"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,8,9]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>A feature selection algorithm may select the subset of features with the best associations with the class labels. The recursive feature elimination (RFE) is a heuristic feature screening framework and has been widely used to select the biological OMIC biomarkers. This study proposed a dynamic recursive feature elimination (dRFE) framework with more flexible feature elimination operations. The proposed dRFE was comprehensively compared with 11 existing feature selection algorithms and five classifiers on the eight difficult transcriptome datasets from a previous study, the ten newly collected transcriptome datasets and the five methylome datasets.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>The experimental data suggested that the regular RFE framework did not perform well, and dRFE outperformed the existing feature selection algorithms in most cases. The dRFE-detected features achieved Acc\u2009=\u20091.0000 for the two methylome datasets GSE53045 and GSE66695. The best prediction accuracies of the dRFE-detected features were 0.9259, 0.9424 and 0.8601 for the other three methylome datasets GSE74845, GSE103186 and GSE80970, respectively. Four transcriptome datasets received Acc\u2009=\u20091.0000 using the dRFE-detected features, and the prediction accuracies for the other six newly collected transcriptome datasets were between 0.6301 and 0.9917.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>The experiments in this study are implemented and tested using the programming language Python version 3.7.6.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Supplementary information<\/jats:title>\n                  <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btab055","type":"journal-article","created":{"date-parts":[[2021,1,25]],"date-time":"2021-01-25T16:04:03Z","timestamp":1611590643000},"page":"2183-2189","source":"Crossref","is-referenced-by-count":42,"title":["A dynamic recursive feature elimination framework (dRFE) to further refine a set of OMIC biomarkers"],"prefix":"10.1093","volume":"37","author":[{"given":"Yuanyuan","family":"Han","sequence":"first","affiliation":[{"name":"College of Computer Science and Technology, and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University , Changchun, Jilin 130012, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lan","family":"Huang","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University , Changchun, Jilin 130012, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8108-6007","authenticated-orcid":false,"given":"Fengfeng","family":"Zhou","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology, and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University , Changchun, Jilin 130012, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2021,1,30]]},"reference":[{"key":"2023061310312496000_btab055-B1","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1038\/35000501","article-title":"Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling","volume":"403","author":"Alizadeh","year":"2000","journal-title":"Nature"},{"key":"2023061310312496000_btab055-B2","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1016\/j.compbiomed.2019.04.017","article-title":"Neural network and support vector machine for the prediction of chronic kidney disease: a comparative study","volume":"109","author":"Almansour","year":"2019","journal-title":"Comput. Biol. Med"},{"key":"2023061310312496000_btab055-B3","doi-asserted-by":"crossref","first-page":"6745","DOI":"10.1073\/pnas.96.12.6745","article-title":"Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays","volume":"96","author":"Alon","year":"1999","journal-title":"Pro. Natl. Acad. Sci. USA"},{"key":"2023061310312496000_btab055-B4","doi-asserted-by":"crossref","first-page":"e16715","DOI":"10.1371\/journal.pone.0016715","article-title":"Autism and increased paternal age related changes in global levels of gene expression regulation","volume":"6","author":"Alter","year":"2011","journal-title":"PLoS One"},{"key":"2023061310312496000_btab055-B5","doi-asserted-by":"crossref","first-page":"400","DOI":"10.1177\/0022034509335868","article-title":"Epigenetics: connecting environment and genotype to phenotype and disease","volume":"88","author":"Barros","year":"2009","journal-title":"J. Dental Res"},{"key":"2023061310312496000_btab055-B6","doi-asserted-by":"crossref","first-page":"11620","DOI":"10.1038\/ncomms11620","article-title":"Epigenetic reprogramming of fallopian tube fimbriae in BRCA mutation carriers defines early ovarian cancer evolution","volume":"7","author":"Bartlett","year":"2016","journal-title":"Nat. Commun"},{"key":"2023061310312496000_btab055-B7","doi-asserted-by":"crossref","first-page":"9939","DOI":"10.1038\/s41598-020-66904-y","article-title":"Prediction of slope failure in open-pit mines using a novel hybrid artificial intelligence model based on decision tree and evolution algorithm","volume":"10","author":"Bui","year":"2020","journal-title":"Sci. Rep"},{"key":"2023061310312496000_btab055-B8","doi-asserted-by":"crossref","first-page":"103381","DOI":"10.1016\/j.compbiomed.2019.103381","article-title":"Detection of major depressive disorder from linear and nonlinear heart rate variability features during mental task protocol","volume":"112","author":"Byun","year":"2019","journal-title":"Comput. Biol. Med"},{"key":"2023061310312496000_btab055-B9","doi-asserted-by":"crossref","first-page":"2771","DOI":"10.1182\/blood-2003-09-3243","article-title":"Gene expression profile of adult T-cell acute lymphocytic leukemia identifies distinct subsets of patients with different response to therapy and survival","volume":"103","author":"Chiaretti","year":"2004","journal-title":"Blood"},{"key":"2023061310312496000_btab055-B10","doi-asserted-by":"crossref","first-page":"1518","DOI":"10.1093\/bioinformatics\/bty828","article-title":"Learning and Imputation for Mass-spec Bias Reduction (LIMBR)","volume":"35","author":"Crowell","year":"2019","journal-title":"Bioinformatics"},{"key":"2023061310312496000_btab055-B11","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1186\/1471-2164-15-151","article-title":"The effect of smoking on DNA methylation of peripheral blood mononuclear cells from African American women","volume":"15","author":"Dogan","year":"2014","journal-title":"BMC Genomics"},{"key":"2023061310312496000_btab055-B12","article-title":"First-trimester prognosis when an early gestational sac is seen on ultrasound imaging: logistic regression prediction model","author":"Doubilet","year":"2020","journal-title":"J. Ultrasound Med"},{"key":"2023061310312496000_btab055-B13","doi-asserted-by":"crossref","first-page":"212","DOI":"10.3389\/fgene.2019.00212","article-title":"Age is important for the early-stage detection of breast cancer on both transcriptomic and methylomic biomarkers","volume":"10","author":"Feng","year":"2019","journal-title":"Front. Genet"},{"key":"2023061310312496000_btab055-B14","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1186\/s12859-016-0990-0","article-title":"McTwo: a two-step feature selection algorithm based on maximal information coefficient","volume":"17","author":"Ge","year":"2016","journal-title":"BMC Bioinf"},{"key":"2023061310312496000_btab055-B15","doi-asserted-by":"crossref","first-page":"531","DOI":"10.1126\/science.286.5439.531","article-title":"Molecular classification of cancer: class discovery and class prediction by gene expression monitoring","volume":"286","author":"Golub","year":"1999","journal-title":"Science"},{"key":"2023061310312496000_btab055-B16","doi-asserted-by":"crossref","first-page":"3681","DOI":"10.1158\/1078-0432.CCR-17-2259","article-title":"BQ323636.1, a novel splice variant to NCOR2, as a predictor for tamoxifen-resistant breast cancer","volume":"24","author":"Gong","year":"2018","journal-title":"Clin. Cancer Res"},{"key":"2023061310312496000_btab055-B17","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1016\/j.ygeno.2013.11.001","article-title":"Gene expression profile based classification models of psoriasis","volume":"103","author":"Guo","year":"2014","journal-title":"Genomics"},{"key":"2023061310312496000_btab055-B18","doi-asserted-by":"crossref","first-page":"1267","DOI":"10.1007\/s00259-015-3303-3","article-title":"Gene signature of the post-Chernobyl papillary thyroid cancer","volume":"43","author":"Handkiewicz-Junak","year":"2016","journal-title":"Eur. J. Nuclear Med. Mol. Imaging"},{"key":"2023061310312496000_btab055-B19","first-page":"1","article-title":"Neighborhood rough set reduction-based gene selection and prioritization for gene expression profile analysis and molecular cancer classification","volume":"2010","author":"Hou","year":"2010","journal-title":"J. Biomed. Biotechnol"},{"key":"2023061310312496000_btab055-B20","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1016\/j.ccell.2017.11.018","article-title":"Genomic and epigenomic profiling of high-risk intestinal metaplasia reveals molecular determinants of progression to gastric cancer","volume":"33","author":"Huang","year":"2018","journal-title":"Cancer Cell"},{"key":"2023061310312496000_btab055-B21","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2015\/943176","article-title":"Genome-wide scan for methylation profiles in keloids","volume":"2015","author":"Jones","year":"2015","journal-title":"Dis. Markers"},{"key":"2023061310312496000_btab055-B22","doi-asserted-by":"crossref","first-page":"544162","DOI":"10.3389\/fgene.2020.544162","article-title":"Next generation sequencing and bioinformatics analysis of family genetic inheritance","volume":"11","author":"Kanzi","year":"2020","journal-title":"Front. Genet"},{"key":"2023061310312496000_btab055-B23","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1038\/nrg.2018.4","article-title":"Integrative omics for health and disease","volume":"19","author":"Karczewski","year":"2018","journal-title":"Nat. Rev. Genet"},{"key":"2023061310312496000_btab055-B24","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2020\/8015156","article-title":"An efficient combination among sMRI, CSF, cognitive score, and APOE epsilon4 biomarkers for classification of AD and MCI using extreme learning machine","volume":"2020","author":"Khatri","year":"2020","journal-title":"Comput. Intell. Neurosci"},{"key":"2023061310312496000_btab055-B25","doi-asserted-by":"crossref","first-page":"1061","DOI":"10.1038\/jcbfm.2012.24","article-title":"TTC7B emerges as a novel risk factor for ischemic stroke through the convergence of several genome-wide approaches","volume":"32","author":"Krug","year":"2012","journal-title":"J. Cerebral Blood Flow Metab"},{"key":"2023061310312496000_btab055-B26","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1186\/1755-8794-4-61","article-title":"Integrating factor analysis and a transgenic mouse model to reveal a peripheral blood predictor of breast tumors","volume":"4","author":"LaBreche","year":"2011","journal-title":"BMC Med. Genomics"},{"key":"2023061310312496000_btab055-B27","doi-asserted-by":"crossref","first-page":"533","DOI":"10.3390\/cancers12030533","article-title":"A splice variant of NCOR2, BQ323636.1, confers chemoresistance in breast cancer by altering the activity of NRF2","volume":"12","author":"Leung","year":"2020","journal-title":"Cancers (Basel)"},{"key":"2023061310312496000_btab055-B28","doi-asserted-by":"crossref","first-page":"593","DOI":"10.1038\/gene.2012.41","article-title":"Transcriptional signatures as a disease-specific and predictive inflammatory biomarker for type 1 diabetes","volume":"13","author":"Levy","year":"2012","journal-title":"Genes Immun"},{"key":"2023061310312496000_btab055-B29","doi-asserted-by":"crossref","first-page":"103667","DOI":"10.1016\/j.compbiomed.2020.103667","article-title":"A new feature selection algorithm based on relevance, redundancy and complementarity","volume":"119","author":"Li","year":"2020","journal-title":"Comput. Biol. Med"},{"key":"2023061310312496000_btab055-B30","doi-asserted-by":"crossref","first-page":"1945","DOI":"10.1093\/bioinformatics\/btm287","article-title":"Logistic regression for disease classification using microarray data: model selection in a large p and small n case","volume":"23","author":"Liao","year":"2007","journal-title":"Bioinformatics"},{"key":"2023061310312496000_btab055-B31","doi-asserted-by":"crossref","first-page":"4615","DOI":"10.1038\/onc.2008.98","article-title":"DNA amplification is a ubiquitous mechanism of oncogene activation in lung and other cancers","volume":"27","author":"Lockwood","year":"2008","journal-title":"Oncogene"},{"key":"2023061310312496000_btab055-B32","doi-asserted-by":"crossref","first-page":"2590","DOI":"10.1158\/1055-9965.EPI-10-0332","article-title":"Identification of a novel biomarker, SEMA5A, for non-small cell lung carcinoma in nonsmoking women","volume":"19","author":"Lu","year":"2010","journal-title":"Cancer Epidemiol. Biomark. Prevent"},{"key":"2023061310312496000_btab055-B33","doi-asserted-by":"crossref","first-page":"3284","DOI":"10.1016\/j.ygeno.2020.06.010","article-title":"An efficient hybrid feature selection method to identify potential biomarkers in common chronic lung inflammatory diseases","volume":"112","author":"Maghsoudloo","year":"2020","journal-title":"Genomics"},{"key":"2023061310312496000_btab055-B34","doi-asserted-by":"crossref","first-page":"2208","DOI":"10.1016\/j.ins.2009.02.014","article-title":"A wrapper method for feature selection using support vector machines","volume":"179","author":"Maldonado","year":"2009","journal-title":"Inf. Sci"},{"key":"2023061310312496000_btab055-B35","doi-asserted-by":"crossref","first-page":"957","DOI":"10.1136\/amiajnl-2014-002974","article-title":"The National Institutes of Health's Big Data to Knowledge (BD2K) initiative: capitalizing on biomedical big data","volume":"21","author":"Margolis","year":"2014","journal-title":"J. Am. Med. Inform. Assoc"},{"key":"2023061310312496000_btab055-B36","first-page":"619","author":"Masaeli","year":"2010"},{"key":"2023061310312496000_btab055-B37","first-page":"1","article-title":"Intra-tumor heterogeneity of gene expression profiles in early stage non-small cell lung cancer","volume":"1","author":"Michael Meister","year":"2014","journal-title":"J. Bioinf. Res. Stud"},{"key":"2023061310312496000_btab055-B38","doi-asserted-by":"crossref","first-page":"13169","DOI":"10.1038\/srep13169","article-title":"Less is more: avoiding the LIBS dimensionality curse through judicious feature selection for explosive detection","volume":"5","author":"Myakalwar","year":"2015","journal-title":"Sci. Rep"},{"key":"2023061310312496000_btab055-B39","doi-asserted-by":"crossref","first-page":"676","DOI":"10.1007\/s10620-018-4929-3","article-title":"Hypermethylation of NF-kappaB-Activating Protein-Like (NKAPL) promoter in hepatocellular carcinoma suppresses its expression and predicts a poor prognosis","volume":"63","author":"Ng","year":"2018","journal-title":"Dig. Dis. Sci"},{"key":"2023061310312496000_btab055-B40","first-page":"3124","article-title":"Transcriptional gene expression profiles of colorectal adenoma, adenocarcinoma, and normal tissue examined by oligonucleotide arrays","volume":"61","author":"Notterman","year":"2001","journal-title":"Cancer Res"},{"key":"2023061310312496000_btab055-B41","doi-asserted-by":"crossref","first-page":"292","DOI":"10.1038\/tpj.2010.56","article-title":"k-Nearest neighbor models for microarray gene expression analysis and clinical outcome prediction","volume":"10","author":"Parry","year":"2010","journal-title":"Pharmacogenomics J"},{"key":"2023061310312496000_btab055-B42","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/415436a","article-title":"Prediction of central nervous system embryonal tumour outcome based on gene expression","volume":"415","author":"Pomeroy","year":"2002","journal-title":"Nature"},{"key":"2023061310312496000_btab055-B43","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1186\/s12859-016-1423-9","article-title":"Minimum redundancy maximum relevance feature selection approach for temporal gene expression data","volume":"18","author":"Radovic","year":"2017","journal-title":"BMC Bioinf"},{"key":"2023061310312496000_btab055-B44","doi-asserted-by":"crossref","first-page":"186ra66","DOI":"10.1126\/scitranslmed.3005723","article-title":"Ectopic activation of germline and placental genes identifies aggressive metastasis-prone lung cancers","volume":"5","author":"Rousseaux","year":"2013","journal-title":"Sci. Transl. Med"},{"key":"2023061310312496000_btab055-B45","doi-asserted-by":"crossref","first-page":"722","DOI":"10.1093\/biostatistics\/kxw018","article-title":"Study design in high-dimensional classification analysis","volume":"17","author":"S\u00e1nchez","year":"2016","journal-title":"Biostatistics"},{"key":"2023061310312496000_btab055-B46","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1586\/erm.13.37","article-title":"Epigenetic biomarkers in laboratory diagnostics: emerging approaches and opportunities","volume":"13","author":"Sandoval","year":"2013","journal-title":"Exp. Rev. Mol. Diagn"},{"key":"2023061310312496000_btab055-B47","doi-asserted-by":"crossref","first-page":"1676","DOI":"10.1212\/WNL.0000000000004516","article-title":"Analysis of blood-based gene expression in idiopathic Parkinson disease","volume":"89","author":"Shamir","year":"2017","journal-title":"Neurology"},{"key":"2023061310312496000_btab055-B48","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1038\/nm0102-68","article-title":"Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning","volume":"8","author":"Shipp","year":"2002","journal-title":"Nat. Med"},{"key":"2023061310312496000_btab055-B49","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1016\/S1535-6108(02)00030-2","article-title":"Gene expression correlates of clinical prostate cancer behavior","volume":"1","author":"Singh","year":"2002","journal-title":"Cancer Cell"},{"key":"2023061310312496000_btab055-B50","doi-asserted-by":"crossref","first-page":"1580","DOI":"10.1016\/j.jalz.2018.01.017","article-title":"Elevated DNA methylation across a 48-kb region spanning the HOXA gene cluster is associated with Alzheimer's disease neuropathology","volume":"14","author":"Smith","year":"2018","journal-title":"Alzheimers Dementia"},{"key":"2023061310312496000_btab055-B51","doi-asserted-by":"crossref","first-page":"696","DOI":"10.1038\/s41568-018-0060-1","article-title":"The COSMIC Cancer Gene Census: describing genetic dysfunction across all human cancers","volume":"18","author":"Sondka","year":"2018","journal-title":"Nat. Rev. Cancer"},{"key":"2023061310312496000_btab055-B52","doi-asserted-by":"crossref","first-page":"1180","DOI":"10.3389\/fgene.2019.01180","article-title":"Master regulators of signaling pathways: an application to the analysis of gene regulation in breast cancer","volume":"10","author":"Tapia-Carrillo","year":"2019","journal-title":"Front. Genet"},{"key":"2023061310312496000_btab055-B53","doi-asserted-by":"crossref","first-page":"2483","DOI":"10.1056\/NEJMoa030847","article-title":"The role of the Wnt-signaling antagonist DKK1 in the development of osteolytic lesions in multiple myeloma","volume":"349","author":"Tian","year":"2003","journal-title":"N. Engl. J. Med"},{"key":"2023061310312496000_btab055-B54","doi-asserted-by":"crossref","first-page":"2444","DOI":"10.1158\/1078-0432.CCR-10-2884","article-title":"Clinical significance of osteoprotegerin expression in human colorectal cancer","volume":"17","author":"Tsukamoto","year":"2011","journal-title":"Clin. Cancer Res"},{"key":"2023061310312496000_btab055-B55","doi-asserted-by":"crossref","first-page":"e63826","DOI":"10.1371\/journal.pone.0063826","article-title":"Comparison of global gene expression of gastric cardia and noncardia cancers from a high-risk population in China","volume":"8","author":"Wang","year":"2013","journal-title":"PLoS One"},{"key":"2023061310312496000_btab055-B56","doi-asserted-by":"crossref","first-page":"1100","DOI":"10.1136\/gutjnl-2011-301373","article-title":"Comprehensive genomic meta-analysis identifies intra-tumoural stroma as a predictor of survival in patients with gastric cancer","volume":"62","author":"Wu","year":"2013","journal-title":"Gut"},{"key":"2023061310312496000_btab055-B57","doi-asserted-by":"crossref","first-page":"105458","DOI":"10.1016\/j.cmpb.2020.105458","article-title":"Prediction model of the response to neoadjuvant chemotherapy in breast cancers by a Naive Bayes algorithm","volume":"192","author":"Yang","year":"2020","journal-title":"Comput. Methods Programs Biomed"},{"key":"2023061310312496000_btab055-B58","doi-asserted-by":"crossref","first-page":"13013","DOI":"10.1038\/s41598-017-13259-6","article-title":"RIFS: a randomly restarted incremental feature selection algorithm","volume":"7","author":"Ye","year":"2017","journal-title":"Sci. Rep"},{"key":"2023061310312496000_btab055-B59","doi-asserted-by":"crossref","first-page":"e55724","DOI":"10.1371\/journal.pone.0055724","article-title":"VCP phosphorylation-dependent interaction partners prevent apoptosis in helicobacter pylori-infected gastric epithelial cells","volume":"8","author":"Yu","year":"2013","journal-title":"PLoS One"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btab055\/36252725\/btab055.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/37\/15\/2183\/50579218\/btab055.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/37\/15\/2183\/50579218\/btab055.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,13]],"date-time":"2023-06-13T10:35:09Z","timestamp":1686652509000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/37\/15\/2183\/6124282"}},"subtitle":[],"editor":[{"given":"Jonathan","family":"Wren","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2021,1,30]]},"references-count":59,"journal-issue":{"issue":"15","published-print":{"date-parts":[[2021,8,9]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btab055","relation":{},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"value":"1367-4803","type":"print"},{"value":"1367-4811","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2021,8,1]]},"published":{"date-parts":[[2021,1,30]]}}}