{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T14:42:40Z","timestamp":1792593760820,"version":"4.5.0"},"reference-count":55,"publisher":"Oxford University Press (OUP)","issue":"10","license":[{"start":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T00:00:00Z","timestamp":1791417600000},"content-version":"vor","delay-in-days":7,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key R&D Program of China","doi-asserted-by":"publisher","award":["2023YFF1205101"],"award-info":[{"award-number":["2023YFF1205101"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,10,2]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>Mendelian randomization (MR) is widely used for causal inference using genetic data, yet most existing MR methods treat exposures as static and have limited capacity to analyze longitudinal measurements. In many biomedical studies, multiple exposures evolve over time, are strongly correlated, and share unobserved temporal structure. Ignoring these features can lead to unstable estimation and reduced power.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We propose factor-augmented multivariable functional Mendelian randomization (FA-MFMR) for estimating time-varying causal effects of multiple longitudinal exposures. FA-MFMR integrates genetic instruments with functional representations of exposure trajectories and a low-dimensional factor structure to capture shared temporal patterns. By separating common temporal variation from exposure-specific components, it mitigates multicollinearity, improves estimation stability, and accommodates sparse causal structures in which some exposures have no effect throughout the observation period. Simulations demonstrate lower estimation error and more efficient uncertainty quantification than competing approaches, particularly for highly correlated and sparsely observed longitudinal exposures. Applied to longitudinal biomarkers in a Parkinson\u2019s disease cohort, FA-MFMR characterizes age-dependent patterns in the estimated trajectory-level coefficient functions while highlighting uncertainty in localized effects.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>The developed R package and code to reproduce all the results are available at https:\/\/github.com\/YQHuFD\/FA-MFMR.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btag725","type":"journal-article","created":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T11:44:09Z","timestamp":1791459849000},"source":"Crossref","is-referenced-by-count":0,"title":["FA-MFMR: a multivariable functional Mendelian randomization method that accounts for correlated longitudinal exposures via factor augmentation"],"prefix":"10.1093","volume":"42","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-5224-3093","authenticated-orcid":false,"given":"Dong","family":"Chen","sequence":"first","affiliation":[{"name":"State Key Laboratory of Genetics and Development of Complex Phenotypes, Institute of Biostatistics, School of Life Sciences, Fudan University , Shanghai, Yangpu District 200438,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junrong","family":"Deng","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Genetics and Development of Complex Phenotypes, Institute of Biostatistics, School of Life Sciences, Fudan University , Shanghai, Yangpu District 200438,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Siyuan","family":"Shen","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Genetics and Development of Complex Phenotypes, Institute of Biostatistics, School of Life Sciences, Fudan University , Shanghai, Yangpu District 200438,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuyang","family":"Zhou","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Genetics and Development of Complex Phenotypes, Institute of Biostatistics, School of Life Sciences, Fudan University , Shanghai, Yangpu District 200438,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hanyu","family":"Cui","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Genetics and Development of Complex Phenotypes, Institute of Biostatistics, School of Life Sciences, Fudan University , Shanghai, Yangpu District 200438,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu","family":"Qiu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Genetics and Development of Complex Phenotypes, Institute of Biostatistics, School of Life Sciences, Fudan University , Shanghai, Yangpu District 200438,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiming","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Genetics and Development of Complex Phenotypes, Institute of Biostatistics, School of Life Sciences, Fudan University , Shanghai, Yangpu District 200438,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5730-0317","authenticated-orcid":false,"given":"Yue-Qing","family":"Hu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Genetics and Development of Complex Phenotypes, Institute of Biostatistics, School of Life Sciences, Fudan University , Shanghai, Yangpu District 200438,","place":["China"]},{"name":"Shanghai Center for Mathematical Sciences, Fudan University , Shanghai, Yangpu District 200438,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2026,10,8]]},"reference":[{"key":"2026102110121909500_btag725-B1","doi-asserted-by":"publisher","first-page":"1203","DOI":"10.3982\/ECTA8968","article-title":"Eigenvalue ratio test for the number of factors","volume":"81","author":"Ahn","year":"2013","journal-title":"Econometrica"},{"key":"2026102110121909500_btag725-B2","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1111\/1468-0262.00392","article-title":"Inferential theory for factor models of large dimensions","volume":"71","author":"Bai","year":"2003","journal-title":"Econometrica"},{"key":"2026102110121909500_btag725-B3","doi-asserted-by":"publisher","first-page":"1351","DOI":"10.1214\/17-EJS1260","article-title":"The function-on-scalar LASSO with applications to longitudinal GWAS","volume":"11","author":"Barber","year":"2017","journal-title":"Electron J Statist"},{"key":"2026102110121909500_btag725-B4","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1002\/mds.29257","article-title":"Blood markers of inflammation, neurodegeneration, and cardiovascular risk in early Parkinson\u2019s disease","volume":"38","author":"Bartl","year":"2023","journal-title":"Mov Disord"},{"key":"2026102110121909500_btag725-B5","doi-asserted-by":"publisher","first-page":"512","DOI":"10.1093\/ije\/dyv080","article-title":"Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression","volume":"44","author":"Bowden","year":"2015","journal-title":"Int J Epidemiol"},{"key":"2026102110121909500_btag725-B6","doi-asserted-by":"publisher","first-page":"658","DOI":"10.1002\/gepi.21758","article-title":"Mendelian randomization analysis with multiple genetic variants using summarized data","volume":"37","author":"Burgess","year":"2013","journal-title":"Genet Epidemiol"},{"key":"2026102110121909500_btag725-B7","doi-asserted-by":"publisher","first-page":"744","DOI":"10.1002\/gepi.22013","article-title":"Mendelian randomization analysis of a time-varying exposure for binary disease outcomes using functional data analysis methods","volume":"40","author":"Cao","year":"2016","journal-title":"Genet Epidemiol"},{"key":"2026102110121909500_btag725-B8","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1186\/s40246-022-00428-6","article-title":"A review on the application of the exposome paradigm to unveil the environmental determinants of age-related diseases","volume":"16","author":"Ding","year":"2022","journal-title":"Hum Genomics"},{"key":"2026102110121909500_btag725-B9","doi-asserted-by":"publisher","first-page":"71","DOI":"10.1016\/j.jeconom.2020.01.006","article-title":"Factor-adjusted regularized model selection","volume":"216","author":"Fan","year":"2020","journal-title":"J Econom"},{"key":"2026102110121909500_btag725-B10","doi-asserted-by":"publisher","first-page":"2129","DOI":"10.1002\/mds.22340","article-title":"Movement Disorder Society-sponsored revision of the Unified Parkinson\u2019s Disease Rating Scale (MDS-UPDRS): scale presentation and clinimetric testing results","volume":"23","author":"Goetz","year":"2008","journal-title":"Mov Disord"},{"key":"2026102110121909500_btag725-B11","doi-asserted-by":"publisher","first-page":"551","DOI":"10.1002\/mds.22379","article-title":"Testing objective measures of motor impairment in early Parkinson\u2019s disease: feasibility study of an at-home testing device","volume":"24","author":"Goetz","year":"2009","journal-title":"Mov Disord"},{"key":"2026102110121909500_btag725-B12","doi-asserted-by":"publisher","first-page":"5813","DOI":"10.1002\/sim.9156","article-title":"Pleiotropy robust methods for multivariable Mendelian randomization","volume":"40","author":"Grant","year":"2021","journal-title":"Stat Med"},{"key":"2026102110121909500_btag725-B13","doi-asserted-by":"publisher","first-page":"262","DOI":"10.1080\/07350015.1996.10524656","article-title":"Finite-sample properties of some alternative GMM estimators","volume":"14","author":"Hansen","year":"1996","journal-title":"J Bus Econ Stat"},{"key":"2026102110121909500_btag725-B14","doi-asserted-by":"publisher","first-page":"42","DOI":"10.3390\/metabo7030042","article-title":"Biomarker research in Parkinson\u2019s disease using metabolite profiling","volume":"7","author":"Havelund","year":"2017","journal-title":"Metabolites"},{"key":"2026102110121909500_btag725-B15","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1038\/s41531-025-01019-7","article-title":"Peripheral inflammation\u2019s variable impact on cognitive and symptomatic outcomes in Parkinson\u2019s disease: a longitudinal and cross-sectional analysis","volume":"11","author":"He","year":"2025","journal-title":"NPJ Parkinsons Dis"},{"key":"2026102110121909500_btag725-B16","doi-asserted-by":"publisher","first-page":"14915","DOI":"10.3390\/ijms241914915","article-title":"Inflammatory blood biomarkers are associated with long-term clinical disease severity in Parkinson\u2019s disease","volume":"24","author":"Hepp","year":"2023","journal-title":"Int J Mol Sci"},{"key":"2026102110121909500_btag725-B17","doi-asserted-by":"publisher","first-page":"e1009723","DOI":"10.1371\/journal.pgen.1009723","article-title":"The impact of age on genetic risk for common diseases","volume":"17","author":"Jiang","year":"2021","journal-title":"PLoS Genet"},{"key":"2026102110121909500_btag725-B18","doi-asserted-by":"publisher","first-page":"811","DOI":"10.3233\/JPD-230007","article-title":"Serum uric acid as a putative biomarker in Prodromal Parkinson\u2019s disease: longitudinal data from the PPMI study","volume":"13","author":"Koros","year":"2023","journal-title":"J Parkinsons Dis"},{"key":"2026102110121909500_btag725-B19","doi-asserted-by":"publisher","first-page":"231","DOI":"10.1093\/aje\/kwy204","article-title":"Interpretation and potential biases of Mendelian randomization estimates with time-varying exposures","volume":"188","author":"Labrecque","year":"2019","journal-title":"Am J Epidemiol"},{"key":"2026102110121909500_btag725-B20","doi-asserted-by":"publisher","first-page":"1133","DOI":"10.1002\/sim.3034","article-title":"Mendelian randomization: using genes as instruments for making causal inferences in epidemiology","volume":"27","author":"Lawlor","year":"2008","journal-title":"Stat Med"},{"key":"2026102110121909500_btag725-B21","doi-asserted-by":"publisher","first-page":"1322228","DOI":"10.3389\/fneur.2024.1322228","article-title":"The neutrophil-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, and neutrophil-tohigh-density-lipoprotein ratio are correlated with the severity of Parkinson\u2019s disease","volume":"15","author":"Li","year":"2024","journal-title":"Front Neurol"},{"key":"2026102110121909500_btag725-B22","doi-asserted-by":"publisher","first-page":"592","DOI":"10.1016\/j.ajhg.2023.02.014","article-title":"Robust multivariable Mendelian randomization based on constrained maximum likelihood","volume":"110","author":"Lin","year":"2023","journal-title":"Am J Hum Genet"},{"key":"2026102110121909500_btag725-B23","doi-asserted-by":"publisher","author":"Ma","year":"2025","DOI":"10.5705\/ss.202025.0205"},{"key":"2026102110121909500_btag725-B24","doi-asserted-by":"publisher","first-page":"1460","DOI":"10.1002\/acn3.644","article-title":"The Parkinson\u2019s progression markers initiative (PPMI)\u2013establishing a PD biomarker cohort","volume":"5","author":"Marek","year":"2018","journal-title":"Ann Clin Transl Neurol"},{"key":"2026102110121909500_btag725-B25","doi-asserted-by":"publisher","first-page":"1240","DOI":"10.1080\/01621459.2023.2183131","article-title":"Instrumental variable estimation of marginal structural mean models for timevarying treatment","volume":"119","author":"Michael","year":"2024","journal-title":"J Am Stat Assoc"},{"key":"2026102110121909500_btag725-B26","doi-asserted-by":"publisher","first-page":"740","DOI":"10.1038\/s41588-020-0631-4","article-title":"Mendelian randomization accounting for correlated and uncorrelated pleiotropic effects using genome-wide summary statistics","volume":"52","author":"Morrison","year":"2020","journal-title":"Nat Genet"},{"key":"2026102110121909500_btag725-B27","doi-asserted-by":"publisher","first-page":"629","DOI":"10.1016\/j.pneurobio.2011.09.005","article-title":"The Parkinson progression marker initiative (PPMI)","volume":"95","author":"Parkinson Progression Marker Initiative","year":"2011","journal-title":"Prog Neurobiol"},{"key":"2026102110121909500_btag725-B28","doi-asserted-by":"publisher","first-page":"e158451","DOI":"10.1172\/JCI158451","article-title":"Metabolic changes in aging humans: current evidence and therapeutic strategies","volume":"132","author":"Palmer","year":"2022","journal-title":"J Clin Invest"},{"key":"2026102110121909500_btag725-B29","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1038\/s41531-023-00626-6","article-title":"Immunological shifts during early-stage Parkinson\u2019s disease identified with DNA methylation data on longitudinally collected blood samples","volume":"10","author":"Pike","year":"2024","journal-title":"NPJ Parkinsons Dis"},{"key":"2026102110121909500_btag725-B30","doi-asserted-by":"publisher","first-page":"501","DOI":"10.1007\/s10654-023-01032-1","article-title":"Methodological approaches, challenges, and opportunities in the application of Mendelian randomisation to lifecourse epidemiology: a systematic literature review","volume":"39","author":"Power","year":"2024","journal-title":"Eur J Epidemiol"},{"key":"2026102110121909500_btag725-B31","doi-asserted-by":"publisher","first-page":"119","DOI":"10.1016\/j.csda.2018.04.003","article-title":"Identification of local sparsity and variable selection for varying coefficient additive hazards models","volume":"125","author":"Qu","year":"2018","journal-title":"Comput Stat Data Anal"},{"key":"2026102110121909500_btag725-B32","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1038\/s41531-023-00449-5","article-title":"A systematic review and metaanalysis of inflammatory biomarkers in Parkinson\u2019s disease","volume":"9","author":"Qu","year":"2023","journal-title":"NPJ Parkinsons Dis"},{"key":"2026102110121909500_btag725-B33","doi-asserted-by":"publisher","first-page":"4705","DOI":"10.1002\/sim.7492","article-title":"Extending the MR-Egger method for multivariable Mendelian randomization to correct for both measured and unmeasured pleiotropy","volume":"36","author":"Rees","year":"2017","journal-title":"Stat Med"},{"key":"2026102110121909500_btag725-B34","doi-asserted-by":"publisher","first-page":"m1203","DOI":"10.1136\/bmj.m1203","article-title":"Use of genetic variation to separate the effects of early and later life adiposity on disease risk: Mendelian randomisation study","volume":"369","author":"Richardson","year":"2020","journal-title":"BMJ"},{"key":"2026102110121909500_btag725-B35","doi-asserted-by":"publisher","first-page":"e84646","DOI":"10.7554\/eLife.84646","article-title":"Time-varying and tissue-dependent effects of adiposity on leptin levels: a Mendelian randomization study","volume":"12","author":"Richardson","year":"2023","journal-title":"Elife"},{"key":"2026102110121909500_btag725-B36","doi-asserted-by":"publisher","first-page":"5434","DOI":"10.1002\/sim.9133","article-title":"Testing and correcting for weak and pleiotropic instruments in two-sample multivariable Mendelian randomization","volume":"40","author":"Sanderson","year":"2021","journal-title":"Stat Med"},{"key":"2026102110121909500_btag725-B37","doi-asserted-by":"publisher","first-page":"e1010290","DOI":"10.1371\/journal.pgen.1010290","article-title":"Estimation of causal effects of a time-varying exposure at multiple time points through multivariable Mendelian randomization","volume":"18","author":"Sanderson","year":"2022","journal-title":"PLoS Genet"},{"key":"2026102110121909500_btag725-B38","doi-asserted-by":"publisher","first-page":"710","DOI":"10.1038\/ng1589","article-title":"An integrative genomics approach to infer causal associations between gene expression and disease","volume":"37","author":"Schadt","year":"2005","journal-title":"Nat Genet"},{"key":"2026102110121909500_btag725-B39","doi-asserted-by":"publisher","first-page":"2173","DOI":"10.1002\/mds.29209","article-title":"Uric acid in Parkinson\u2019s disease: what is the connection?","volume":"37","author":"Seifar","year":"2022","journal-title":"Mov Disord"},{"key":"2026102110121909500_btag725-B40","doi-asserted-by":"publisher","first-page":"3547","DOI":"10.1002\/sim.9819","article-title":"Instrumental variable model average with applications in Mendelian randomization","volume":"42","author":"Seng","year":"2023","journal-title":"Stat Med"},{"key":"2026102110121909500_btag725-B41","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1097\/EDE.0000000000001417","article-title":"Mendelian randomization with repeated measures of a time-varying exposure: an application of structural mean models","volume":"33","author":"Shi","year":"2022","journal-title":"Epidemiology"},{"key":"2026102110121909500_btag725-B42","doi-asserted-by":"publisher","first-page":"382","DOI":"10.1136\/jech.2004.031880","article-title":"Randomised by (your) god: robust inference from an observational study design","volume":"60","author":"Smith","year":"2006","journal-title":"J Epidemiol Community Health"},{"key":"2026102110121909500_btag725-B43","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1093\/ije\/dyg070","article-title":"\u2018Mendelian randomization\u2019: can genetic epidemiology contribute to understanding environmental determinants of disease?","volume":"32","author":"Smith","year":"2003","journal-title":"Int J Epidemiol"},{"key":"2026102110121909500_btag725-B44","doi-asserted-by":"publisher","first-page":"723","DOI":"10.1007\/s10654-018-0396-6","article-title":"Causal null hypotheses of sustained treatment strategies: what can be tested with an instrumental variable?","volume":"33","author":"Swanson","year":"2018","journal-title":"Eur J Epidemiol"},{"key":"2026102110121909500_btag725-B45","doi-asserted-by":"publisher","first-page":"846","DOI":"10.1093\/ije\/dyac240","article-title":"Estimation of time-varying causal effects with multivariable Mendelian randomization: some cautionary notes","volume":"52","author":"Tian","year":"2023","journal-title":"Int J Epidemiol"},{"key":"2026102110121909500_btag725-B46","doi-asserted-by":"publisher","first-page":"5166","DOI":"10.1002\/sim.10222","article-title":"Estimating time-varying exposure effects through continuous-time modelling in Mendelian randomization","volume":"43","author":"Tian","year":"2024","journal-title":"Stat Med"},{"key":"2026102110121909500_btag725-B47","doi-asserted-by":"publisher","first-page":"e1009575","DOI":"10.1371\/journal.pgen.1009575","article-title":"Causal inference for heritable phenotypic risk factors using heterogeneous genetic instruments","volume":"17","author":"Wang","year":"2021","journal-title":"PLoS Genet"},{"key":"2026102110121909500_btag725-B48","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1146\/annurev-statistics-041715-033624","article-title":"Functional data analysis","volume":"3","author":"Wang","year":"2016","journal-title":"Annu Rev Stat Appl"},{"key":"2026102110121909500_btag725-B49","doi-asserted-by":"publisher","first-page":"6945","DOI":"10.1038\/s41467-025-61648-7","article-title":"Causal mediation analysis for time-varying heritable risk factors with Mendelian randomization","volume":"16","author":"Wu","year":"2025","journal-title":"Nat Commun"},{"key":"2026102110121909500_btag725-B50","doi-asserted-by":"publisher","first-page":"1251","DOI":"10.1016\/j.ajhg.2021.05.014","article-title":"Constrained maximum likelihoodbased Mendelian randomization robust to both correlated and uncorrelated pleiotropic effects","volume":"108","author":"Xue","year":"2021","journal-title":"Am J Hum Genet"},{"key":"2026102110121909500_btag725-B51","doi-asserted-by":"publisher","first-page":"577","DOI":"10.1198\/016214504000001745","article-title":"Functional data analysis for sparse longitudinal data","volume":"100","author":"Yao","year":"2005","journal-title":"J Am Stat Assoc"},{"key":"2026102110121909500_btag725-B52","doi-asserted-by":"publisher","first-page":"e70394","DOI":"10.1002\/sim.70394","article-title":"Mendelian randomization methods for causal inference: estimands, identification and inference","volume":"45","author":"Yao","year":"2026","journal-title":"Stat Med"},{"key":"2026102110121909500_btag725-B53","doi-asserted-by":"publisher","first-page":"1045","DOI":"10.1093\/jrsssb\/qkae024","article-title":"GENIUS-MAWII: for robust Mendelian randomization with many weak invalid instruments","volume":"86","author":"Ye","year":"2024","journal-title":"J R Stat Soc Series B Stat Methodol"},{"key":"2026102110121909500_btag725-B54","author":"Zhang","year":"2026"},{"key":"2026102110121909500_btag725-B55","doi-asserted-by":"publisher","first-page":"605","DOI":"10.1086\/512821","article-title":"Overcoming the winner\u2019s curse: estimating penetrance parameters from case-control data","volume":"80","author":"Z\u00f6llner","year":"2007","journal-title":"Am J Hum Genet"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btag725\/71718121\/btag725.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/42\/10\/btag725\/71718121\/btag725.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/42\/10\/btag725\/71718121\/btag725.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T14:12:26Z","timestamp":1792591946000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/doi\/10.1093\/bioinformatics\/btag725\/8885528"}},"subtitle":[],"editor":[{"given":"Lenore","family":"Cowen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2026,10]]},"references-count":55,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2026,10,2]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btag725","relation":{},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"value":"1367-4803","type":"print"},{"value":"1367-4811","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2026,10]]},"published":{"date-parts":[[2026,10]]},"article-number":"btag725"}}