{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,22]],"date-time":"2026-02-22T03:01:49Z","timestamp":1771729309868,"version":"3.50.1"},"reference-count":74,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2025,6,20]],"date-time":"2025-06-20T00:00:00Z","timestamp":1750377600000},"content-version":"vor","delay-in-days":50,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"Scientific Foundation of the Spanish Association Against Cancer","award":["PERME224336TARA"],"award-info":[{"award-number":["PERME224336TARA"]}]},{"DOI":"10.13039\/501100004587","name":"Instituto de Salud Carlos III","doi-asserted-by":"publisher","award":["AC22\/00058"],"award-info":[{"award-number":["AC22\/00058"]}],"id":[{"id":"10.13039\/501100004587","id-type":"DOI","asserted-by":"publisher"}]},{"name":"ERA PerMed","award":["ERAPERMED2022-141"],"award-info":[{"award-number":["ERAPERMED2022-141"]}]},{"name":"FP7 STATegra project","award":["306000"],"award-info":[{"award-number":["306000"]}]},{"name":"Spanish MINECO","award":["BIO2012-40244"],"award-info":[{"award-number":["BIO2012-40244"]}]},{"name":"Spanish MICIN","award":["PID2020-119537RB-100"],"award-info":[{"award-number":["PID2020-119537RB-100"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,5,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Studying phenotype-specific regulatory mechanisms is crucial to understanding the molecular basis of diseases and other complex traits. However, existing approaches for constructing multi-omic regulatory networks MO-RN are scarce, and most cannot integrate diverse omics modalities, incorporate prior biological knowledge, or infer phenotype-specific networks. To address these challenges, we present MORE (Multi-Omics REgulation), a novel R package for inferring multi-modal regulatory networks. MORE is available at https:\/\/github.com\/BiostatOmics\/MORE and supports any number and type of omics layers while optionally incorporating prior regulatory knowledge. Leveraging advanced regression-based models and variable selection techniques, MORE identifies significant regulatory relationships. This tool also provides useful functionalities for the biological interpretation of MO-RN: network visualisations, differential regulatory networks, and functional enrichment analyses of key network features. We evaluated MORE on simulated multi-omic datasets and benchmarked it against state-of-the-art tools. Our tool consistently outperformed other methods regarding accuracy in identifying significant regulators, model goodness-of-fit, and computational efficiency. We further applied MORE to a multi-omic ovarian cancer dataset to uncover tumour subtype-specific regulatory mechanisms associated with distinct survival outcomes. This analysis revealed differential regulatory patterns to understand the molecular basis of each subtype. By addressing the limitations of methods for multi-omic network inference, MORE represents a valuable resource for studying regulatory systems. Its ability to construct phenotype-specific regulatory networks with high accuracy and interpretability positions it as a useful resource for researchers seeking to unravel the complexities of molecular interactions and regulatory mechanisms across diverse biological contexts.<\/jats:p>","DOI":"10.1093\/bib\/bbaf270","type":"journal-article","created":{"date-parts":[[2025,6,27]],"date-time":"2025-06-27T22:09:36Z","timestamp":1751062176000},"source":"Crossref","is-referenced-by-count":3,"title":["MORE interpretable multi-omic regulatory networks to characterise phenotypes"],"prefix":"10.1093","volume":"26","author":[{"given":"Maider","family":"Aguerralde-Martin","sequence":"first","affiliation":[{"name":"Department of Applied Statistics , Operational Research and Quality, Universitat Polit\u00e8cnica de Val\u00e8ncia, Cam\u00ed de Vera s\/n, Valencia 46022,","place":["Spain"]}]},{"given":"M\u00f3nica","family":"Clemente-C\u00edscar","sequence":"additional","affiliation":[{"name":"Igenomix , Ronda Narciso Monturiol, Parque tecnol\u00f3gico Paterna, Paterna 46980,","place":["Spain"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9597-311X","authenticated-orcid":false,"given":"Ana","family":"Conesa","sequence":"additional","affiliation":[{"name":"Genomics of Gene Expression Lab , Institute for Integrative Systems Biology, Spanish National Research Council (CSIC-UV), Catedr\u00e0tic Agust\u00edn Escardino Benlloch, Paterna 46980,","place":["Spain"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5346-1407","authenticated-orcid":false,"given":"Sonia","family":"Tarazona","sequence":"additional","affiliation":[{"name":"Department of Applied Statistics , Operational Research and Quality, Universitat Polit\u00e8cnica de Val\u00e8ncia, Cam\u00ed de Vera s\/n, Valencia 46022,","place":["Spain"]}]}],"member":"286","published-online":{"date-parts":[[2025,6,20]]},"reference":[{"key":"2025062718093093400_ref1","doi-asserted-by":"publisher","first-page":"bbab024","DOI":"10.1093\/bib\/bbab024","article-title":"Advances in bulk and single-cell multi-omics approaches for systems biology and precision medicine","volume":"22","author":"Li","year":"2021","journal-title":"Brief Bioinform"},{"key":"2025062718093093400_ref2","doi-asserted-by":"publisher","first-page":"515","DOI":"10.1038\/s12276-024-01186-2","article-title":"Advances in single-cell omics and multiomics for high-resolution molecular profiling","volume":"56","author":"Lim","year":"2024","journal-title":"Exp Mol Med"},{"key":"2025062718093093400_ref3","doi-asserted-by":"publisher","first-page":"559","DOI":"10.1186\/1471-2105-9-559","article-title":"WGCNA: an R package for weighted correlation network analysis","volume":"9","author":"Langfelder","year":"2008","journal-title":"BMC Bioinformatics"},{"key":"2025062718093093400_ref4","doi-asserted-by":"publisher","first-page":"S7","DOI":"10.1186\/1471-2105-7-S1-S7","article-title":"ARACNE: an algorithm for the reconstruction of gene regulatory networks in a mammalian cellular context","volume":"7","author":"Margolin","year":"2006","journal-title":"BMC Bioinformatics"},{"key":"2025062718093093400_ref5","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1186\/1471-2105-12-243","article-title":"RegNetB: predicting relevant regulator-gene relationships in localized prostate tumor samples","volume":"12","author":"Alvarez","year":"2011","journal-title":"BMC Bioinformatics"},{"key":"2025062718093093400_ref6","doi-asserted-by":"publisher","first-page":"1776","DOI":"10.1093\/bioinformatics\/btt290","article-title":"Differential network analysis for the identification of condition-specific pathway activity and regulation","volume":"29","author":"Gambardella","year":"2013","journal-title":"Bioinformatics"},{"key":"2025062718093093400_ref7","doi-asserted-by":"publisher","first-page":"Article15","DOI":"10.2202\/1544-6115.1282","article-title":"Reconstructing gene regulatory networks with bayesian networks by combining expression data with multiple sources of prior knowledge","volume":"6","author":"Werhli","year":"2007","journal-title":"Stat Appl Genet Mol Biol"},{"key":"2025062718093093400_ref8","doi-asserted-by":"publisher","first-page":"3413","DOI":"10.1093\/bioinformatics\/btv406","article-title":"DINGO: differential network analysis in genomics","volume":"31","author":"Ha","year":"2015","journal-title":"Bioinformatics"},{"key":"2025062718093093400_ref9","doi-asserted-by":"publisher","first-page":"441","DOI":"10.1093\/bfgp\/elac028","article-title":"PGRNIG: novel parallel gene regulatory network identification algorithm based on GPU","volume":"21","author":"Yang","year":"2022","journal-title":"Brief Funct Genomics"},{"key":"2025062718093093400_ref10","doi-asserted-by":"publisher","first-page":"888786","DOI":"10.3389\/fgene.2022.888786","article-title":"Gene regulatory identification based on the novel hybrid time-delayed method","volume":"13","author":"Bao","year":"2022","journal-title":"Front Genet"},{"key":"2025062718093093400_ref11","doi-asserted-by":"publisher","first-page":"117793221989905","DOI":"10.1177\/1177932219899051","article-title":"Multi-omics data integration, interpretation, and its application","volume":"14","author":"Subramanian","year":"2020","journal-title":"Bioinform Biol Insights"},{"key":"2025062718093093400_ref12","doi-asserted-by":"publisher","DOI":"10.1093\/bib\/bbab024","article-title":"Advances in bulk and single-cell multi-omics approaches for systems biology and precision medicine","volume":"22","author":"Yunjin, Li","year":"2021","journal-title":"Brief Bioinform"},{"key":"2025062718093093400_ref13","doi-asserted-by":"publisher","first-page":"549","DOI":"10.1093\/bfgp\/elae013","article-title":"A comprehensive review of machine learning techniques for multi-omics data integration: challenges and applications in precision oncology","volume":"23","author":"Acharya","year":"2024","journal-title":"Brief Funct Genomics"},{"key":"2025062718093093400_ref14","doi-asserted-by":"publisher","first-page":"6806","DOI":"10.1038\/s41598-021-85544-4","article-title":"Versatile knowledge guided network inference method for prioritizing key regulatory factors in multi-omics data","volume":"11","author":"Ogris","year":"2021","journal-title":"Sci Rep"},{"key":"2025062718093093400_ref15","doi-asserted-by":"publisher","first-page":"395","DOI":"10.1038\/s43588-021-00086-z","article-title":"Undisclosed, unmet and neglected challenges in multi-omics studies","volume":"1","author":"Tarazona","year":"2021","journal-title":"Nature Computational Science"},{"key":"2025062718093093400_ref16","doi-asserted-by":"publisher","first-page":"e1011920","DOI":"10.1371\/journal.pcbi.1011920","article-title":"For long-term sustainable software in bioinformatics","volume":"20","author":"Coelho","year":"2024","journal-title":"PLoS Comput Biol"},{"key":"2025062718093093400_ref17","doi-asserted-by":"publisher","first-page":"238","DOI":"10.1109\/BIBE.2014.71","article-title":"Integration of dna methylation, copy number variation, and gene expression for gene regulatory network inference and application to psychiatric disorders","volume-title":"IEEE International Conference on Bioinformatics and Bioengineering","author":"Kim"},{"key":"2025062718093093400_ref18","doi-asserted-by":"publisher","first-page":"782","DOI":"10.1109\/TCBB.2018.2866836","article-title":"Integration of multi-omics data for gene regulatory network inference and application to breast cancer","volume":"16","author":"Yuan","year":"2019","journal-title":"IEEE\/ACM Trans Comput Biol Bioinform"},{"key":"2025062718093093400_ref19","doi-asserted-by":"publisher","first-page":"1165","DOI":"10.1093\/bioinformatics\/btab722","article-title":"MoNET: an R package for multi-omic network analysis","volume":"38","author":"Li","year":"2021","journal-title":"Bioinformatics"},{"key":"2025062718093093400_ref20","doi-asserted-by":"publisher","first-page":"W283","DOI":"10.1093\/nar\/gkv418","article-title":"TFmiR: a web server for constructing and analyzing disease-specific transcription factor and mirna co-regulatory networks","volume":"43","author":"Hamed","year":"2015","journal-title":"Nucleic Acids Res"},{"key":"2025062718093093400_ref21","doi-asserted-by":"publisher","first-page":"1124","DOI":"10.1093\/bioinformatics\/btu748","article-title":"SAMNetWeb: identifying condition-specific networks linking signaling and transcription","volume":"31","author":"Gosline","year":"2014","journal-title":"Bioinformatics"},{"key":"2025062718093093400_ref22","doi-asserted-by":"publisher","first-page":"569","DOI":"10.1089\/cmb.2022.0149","article-title":"IntOMICS: a bayesian framework for reconstructing regulatory networks using multi-omics data","volume":"30","author":"Pa\u010d\u00ednkov\u00e1","year":"2023","journal-title":"J Comput Biol"},{"key":"2025062718093093400_ref23","doi-asserted-by":"publisher","first-page":"e1003908","DOI":"10.1371\/journal.pcbi.1003908","article-title":"Regression analysis of combined gene expression regulation in acute myeloid leukemia","volume":"10","author":"Li","year":"2014","journal-title":"PLoS Comput Biol"},{"key":"2025062718093093400_ref24","doi-asserted-by":"publisher","first-page":"1243","DOI":"10.1093\/bioinformatics\/btx750","article-title":"iDINGO\u2014Integrative differential network analysis in genomics with shiny application","volume":"34","author":"Class","year":"2017","journal-title":"Bioinformatics"},{"key":"2025062718093093400_ref25","doi-asserted-by":"publisher","first-page":"e8124","DOI":"10.15252\/msb.20178124","article-title":"Multi-omics factor analysis-a framework for unsupervised integration of multi-omics data sets","volume":"14","author":"Argelaguet","year":"2018","journal-title":"Mol Syst Biol"},{"key":"2025062718093093400_ref26","doi-asserted-by":"publisher","first-page":"e1005752","DOI":"10.1371\/journal.pcbi.1005752","article-title":"Mixomics: an r package for \u2018omics feature selection and multiple data integration","volume":"13","author":"Rohart","year":"2017","journal-title":"PLoS Comput Biol"},{"key":"2025062718093093400_ref27","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1186\/s12859-021-04016-8","article-title":"Cantare: finding and visualizing network-based multi-omic predictive models","volume":"22","author":"Siebert","year":"2021","journal-title":"BMC Bioinformatics"},{"key":"2025062718093093400_ref28","doi-asserted-by":"publisher","DOI":"10.1093\/bib\/bbad309","article-title":"Multi-omics regulatory network inference in the presence of missing data","volume":"24","author":"Henao","year":"2023","journal-title":"Brief Bioinform"},{"key":"2025062718093093400_ref29","article-title":"PLS-regression: A basic tool of chemometrics","volume-title":"Chemometr Intell Lab Search","author":""},{"key":"2025062718093093400_ref30","doi-asserted-by":"publisher","first-page":"301","DOI":"10.1111\/j.1467-9868.2005.00503.x","article-title":"Regularization and variable selection via the elastic net","volume":"67","author":"Zou","year":"2005","journal-title":"J R Stat Soc Series B Stat Methodology"},{"key":"2025062718093093400_ref31","doi-asserted-by":"publisher","first-page":"722","DOI":"10.1080\/10618600.2019.1573687","article-title":"An iterative sparse-group lasso","volume":"28","author":"Laria","year":"2019","journal-title":"J Comput Graph Stat"},{"key":"2025062718093093400_ref32","first-page":"263","article-title":"Multi-and megavariate data analysis: finding and using regularities in metabonomics data","volume-title":"Metabolomics in Toxicity Assessment","author":"Eriksson"},{"key":"2025062718093093400_ref33","doi-asserted-by":"publisher","first-page":"231","DOI":"10.1080\/10618600.2012.681250","article-title":"A sparse-group lasso","volume":"22","author":"Simon","year":"2013","journal-title":"J Comput Graph Stat"},{"key":"2025062718093093400_ref34","doi-asserted-by":"publisher","DOI":"10.3390\/math9030222","article-title":"Iterative variable selection for high-dimensional data: prediction of pathological response in triple-negative breast cancer","volume":"9","author":"Laria","year":"2021","journal-title":"Mathematics"},{"key":"2025062718093093400_ref35","doi-asserted-by":"publisher","DOI":"10.1016\/B978-0-12-426653-7.50032-6","article-title":"Nonlinear iterative partial least squares (nipals) modelling: some current developments","volume-title":"Multivariate Analysis\u2013III","author":"Wold"},{"key":"2025062718093093400_ref36","doi-asserted-by":"publisher","first-page":"3322","DOI":"10.1021\/acs.jproteome.5b00354","article-title":"Analysis of the human adult urinary metabolome variations with age, body mass index, and gender by implementing a comprehensive workflow for univariate and opls statistical analyses","volume":"14","author":"Th\u00e9venot","year":"2015","journal-title":"J Proteome Res"},{"key":"2025062718093093400_ref37","doi-asserted-by":"publisher","first-page":"2498","DOI":"10.1101\/gr.1239303","article-title":"Cytoscape: a software environment for integrated models of biomolecular interaction networks","volume":"13","author":"Shannon","year":"2003","journal-title":"Genome Res"},{"key":"2025062718093093400_ref38","doi-asserted-by":"publisher","first-page":"03","DOI":"10.1093\/bib\/bbaf110","article-title":"MOSim: bulk and single-cell multilayer regulatory network simulator","volume":"26","author":"Monz\u00f3","year":"2025","journal-title":"Brief Bioinform"},{"key":"2025062718093093400_ref39","doi-asserted-by":"publisher","first-page":"609","DOI":"10.1038\/nature10166","article-title":"Integrated genomic analyses of ovarian carcinoma","volume":"474","author":"Cancer Genome Atlas Research Network","year":"2012","journal-title":"Nature."},{"key":"2025062718093093400_ref40","doi-asserted-by":"publisher","first-page":"e140","DOI":"10.1093\/nar\/gkv711","article-title":"Data quality aware analysis of differential expression in rna-seq with noiseq r\/bioc package","volume":"43","author":"Tarazona","year":"2015","journal-title":"Nucleic Acids Res"},{"key":"2025062718093093400_ref41","doi-asserted-by":"publisher","first-page":"baac083","DOI":"10.1093\/database\/baac083","article-title":"TFlink: an integrated gateway to access transcription factor-target gene interactions for multiple species","volume":"2022","author":"Liska","year":"2022","journal-title":"Database (Oxford)"},{"key":"2025062718093093400_ref42","article-title":"HumanMethylation27 product support files","author":"Illumina"},{"key":"2025062718093093400_ref43","doi-asserted-by":"publisher","first-page":"e0206239","DOI":"10.1371\/journal.pone.0206239","article-title":"Mirwalk: An online resource for prediction of microrna binding sites","volume":"13","author":"Sticht","year":"2018","journal-title":"PloS One"},{"key":"2025062718093093400_ref44","doi-asserted-by":"publisher","first-page":"557","DOI":"10.1093\/qje\/qjy029","article-title":"Channeling fisher: Randomization tests and the statistical insignificance of seemingly significant experimental results$\\ast $","volume":"134","author":"Young","year":"2018","journal-title":"The Quarterly Journal of Economics"},{"key":"2025062718093093400_ref45","doi-asserted-by":"publisher","first-page":"414","DOI":"10.1080\/15384101.2017.1376150","article-title":"Double duty: Zmynd8 in the dna damage response and cancer","volume":"17","author":"Gong","year":"2018","journal-title":"Cell Cycle"},{"key":"2025062718093093400_ref46","doi-asserted-by":"publisher","first-page":"683","DOI":"10.1038\/s41416-018-0217-4","article-title":"BRCA1 and BRCA2 mRNA-expression prove to be of clinical impact in ovarian cancer","volume":"119","author":"Tsibulak","year":"2018","journal-title":"Br J Cancer"},{"key":"2025062718093093400_ref47","doi-asserted-by":"publisher","first-page":"2402","DOI":"10.1001\/jama.2017.7112","article-title":"Risks of breast, ovarian, and contralateral breast cancer for brca1 and brca2 mutation carriers","volume":"317","author":"Kuchenbaecker","year":"2017","journal-title":"Jama"},{"key":"2025062718093093400_ref48","doi-asserted-by":"publisher","first-page":"1117","DOI":"10.1086\/375033","article-title":"Average risks of breast and ovarian cancer associated with brca1 or brca2 mutations detected in case series unselected for family history: a combined analysis of 22 studies","volume":"72","author":"Antoniou","year":"2003","journal-title":"The American Journal of Human Genetics"},{"key":"2025062718093093400_ref49","doi-asserted-by":"publisher","first-page":"1329","DOI":"10.1200\/JCO.2006.09.1066","article-title":"Meta-analysis of brca1 and brca2 penetrance","volume":"25","author":"Chen","year":"2007","journal-title":"J Clin Oncol Off J Am Soc Clin Oncol"},{"key":"2025062718093093400_ref50","doi-asserted-by":"publisher","first-page":"375","DOI":"10.1016\/j.ygyno.2017.08.030","article-title":"Frequency of mutations in a large series of clinically ascertained ovarian cancer cases tested on multi-gene panels compared to reference controls","volume":"147","author":"Lilyquist","year":"2017","journal-title":"Gynecol Oncol"},{"key":"2025062718093093400_ref51","doi-asserted-by":"publisher","first-page":"452","DOI":"10.1016\/j.ygyno.2019.01.027","article-title":"Large-scale meta-analysis of mutations identified in panels of breast\/ovarian cancer-related genes\u2014providing evidence of cancer predisposition genes","volume":"153","author":"Suszynska","year":"2019","journal-title":"Gynecol Oncol"},{"key":"2025062718093093400_ref52","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1186\/s13048-020-00654-3","article-title":"BRIP1, RAD51C, and RAD51D mutations are associated with high susceptibility to ovarian cancer: mutation prevalence and precise risk estimates based on a pooled analysis of 30,000 cases","volume":"13","author":"Suszynska","year":"2020","journal-title":"J Ovarian Res"},{"key":"2025062718093093400_ref53","doi-asserted-by":"publisher","first-page":"843","DOI":"10.1080\/15384047.2019.1579955","article-title":"Clinical importance of FANCD2, BRIP1, BRCA1, BRCA2 and FANCF expression in ovarian carcinomas","volume":"20","author":"Moes-Sosnowska","year":"2019","journal-title":"Cancer Biol Ther"},{"key":"2025062718093093400_ref54","doi-asserted-by":"publisher","first-page":"1077","DOI":"10.1016\/j.devcel.2011.10.010","article-title":"Oncogenic RAS regulates BRIP1 expression to induce dissociation of BRCA1 from chromatin, inhibit DNA repair, and promote senescence","volume":"21","author":"Tu","year":"2011","journal-title":"Dev Cell"},{"key":"2025062718093093400_ref55","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2023\/4104639","article-title":"Insights into the oncogenic, prognostic, and immunological role of brip1 in pan-cancer: a comprehensive data-mining-based study","volume":"2023","author":"Liu","year":"2023","journal-title":"J Oncol"},{"key":"2025062718093093400_ref56","doi-asserted-by":"publisher","first-page":"216","DOI":"10.1016\/j.ygyno.2020.05.353","article-title":"The role of ccne1 amplification in refractory ovarian and endometrial cancer","volume":"159","author":"Park","year":"2020","journal-title":"Gynecol Oncol"},{"key":"2025062718093093400_ref57","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1016\/j.gore.2018.01.005","article-title":"Clonal lineage of high grade serous ovarian cancer in a patient with neurofibromatosis type 1","volume":"23","author":"Norris","year":"2018","journal-title":"Gynecologic Oncology Reports"},{"key":"2025062718093093400_ref58","doi-asserted-by":"publisher","first-page":"018","DOI":"10.7554\/eLife.39030","article-title":"Targeting ref58 dependency in ovarian cancer through inhibition of CDK7 and CDK12\/13","volume":"7","author":"Zeng","journal-title":"Elife"},{"key":"2025062718093093400_ref59","doi-asserted-by":"publisher","first-page":"245","DOI":"10.1002\/cac2.12274","article-title":"The fibrillin-1\/VEGFR2\/STAT2 signaling axis promotes chemoresistance via modulating glycolysis and angiogenesis in ovarian cancer organoids and cells","volume":"42","author":"Wang","year":"2022","journal-title":"Cancer Commun"},{"key":"2025062718093093400_ref60","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1016\/j.ygyno.2004.08.047","article-title":"Clinical applications of microarray technology: Creatine kinase B is an up-regulated gene in epithelial ovarian cancer and shows promise as a serum marker","volume":"96","author":"Huddleston","year":"2005","journal-title":"Gynecol Oncol"},{"key":"2025062718093093400_ref61","doi-asserted-by":"publisher","first-page":"1275","DOI":"10.2147\/OTT.S154517","article-title":"Microrna 302b-3p\/302c-3p\/302d-3p inhibits epithelial\u2013mesenchymal transition and promotes apoptosis in human endometrial carcinoma cells","volume":"11","author":"Li","year":"2018","journal-title":"Onco Targets Ther"},{"key":"2025062718093093400_ref62","doi-asserted-by":"publisher","first-page":"1069","DOI":"10.1002\/cbf.3544","article-title":"LncRNA TUG1 facilitates proliferation, invasion and stemness of ovarian cancer cell via miR-186-5p\/ZEB1 axis","volume":"38","author":"Zhan","year":"2020","journal-title":"Cell Biochem Funct"},{"key":"2025062718093093400_ref63","doi-asserted-by":"publisher","first-page":"2796","DOI":"10.1002\/1878-0261.12762","article-title":"Epithelial\/mesenchymal heterogeneity of high-grade serous ovarian carcinoma samples correlates with miRNA let-7 levels and predicts tumor growth and metastasis","volume":"14","author":"Chirshev","year":"2020","journal-title":"Mol Oncol"},{"key":"2025062718093093400_ref64","doi-asserted-by":"publisher","first-page":"328","DOI":"10.7497\/j.issn.2095-3941.2015.0024","article-title":"microRNA: a new and promising potential biomarker for diagnosis and prognosis of ovarian cancer","volume":"12","author":"Pal","year":"2015","journal-title":"Cancer Biol Med"},{"key":"2025062718093093400_ref65","doi-asserted-by":"publisher","first-page":"894","DOI":"10.1101\/gad.1640608","article-title":"The miR-200 family determines the epithelial phenotype of cancer cells by targeting the e-cadherin repressors ZEB1 and ZEB2","volume":"22","author":"Park","year":"2008","journal-title":"Genes Dev"},{"key":"2025062718093093400_ref66","doi-asserted-by":"publisher","first-page":"609","DOI":"10.1038\/nature10166","article-title":"Integrated genomic analyses of ovarian carcinoma","volume":"474","year":"2011","journal-title":"Nature"},{"key":"2025062718093093400_ref67","doi-asserted-by":"publisher","DOI":"10.3390\/ijms232213777","article-title":"Molecular management of high-grade serous ovarian carcinoma","volume":"23","author":"Punz\u00f3n-Jim\u00e9nez","year":"2022","journal-title":"Int J Mol Sci"},{"key":"2025062718093093400_ref68","doi-asserted-by":"publisher","DOI":"10.3390\/cancers13123065","article-title":"FOXM1: a multifunctional oncoprotein and emerging therapeutic target in ovarian cancer","volume":"13","author":"Liu","year":"2021","journal-title":"Cancers (Basel)"},{"key":"2025062718093093400_ref69","doi-asserted-by":"publisher","first-page":"3384","DOI":"10.1038\/onc.2016.487","article-title":"An integrated analysis identifies STAT4 as a key regulator of ovarian cancer metastasis","volume":"36","author":"Zhao","year":"2017","journal-title":"Oncogene"},{"key":"2025062718093093400_ref70","doi-asserted-by":"publisher","first-page":"348","DOI":"10.1016\/j.ygyno.2016.02.030","article-title":"High expression of orphan nuclear receptor NR4A1 in a subset of ovarian tumors with worse outcome","volume":"141","author":"Delgado","year":"2016","journal-title":"Gynecol Oncol"},{"key":"2025062718093093400_ref71","doi-asserted-by":"publisher","DOI":"10.1093\/jnci\/dju249","article-title":"Prognostic and therapeutic relevance of molecular subtypes in high-grade serous ovarian cancer","volume":"106","author":"Konecny","year":"2014","journal-title":"J Natl Cancer Inst"},{"key":"2025062718093093400_ref72","doi-asserted-by":"publisher","first-page":"83476","DOI":"10.18632\/oncotarget.13080","article-title":"Autophagy as an emerging therapy target for ovarian carcinoma","volume":"7","author":"Zhan","year":"2016","journal-title":"Oncotarget"},{"key":"2025062718093093400_ref73","doi-asserted-by":"publisher","first-page":"e22362","DOI":"10.1096\/fj.202101993RR","article-title":"Citric acid of ovarian cancer metabolite induces pyroptosis via the caspase-4\/TXNIP-NLRP3-GSDMD pathway in ovarian cancer","volume":"36","author":"Wang","year":"2022","journal-title":"FASEB J"},{"key":"2025062718093093400_ref74","doi-asserted-by":"publisher","first-page":"216","DOI":"10.1007\/s13238-017-0451-1","article-title":"The emerging role and targetability of the TCA cycle in cancer metabolism","volume":"9","author":"Anderson","year":"2018","journal-title":"Protein Cell"}],"container-title":["Briefings in Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/26\/3\/bbaf270\/63529605\/bbaf270.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/26\/3\/bbaf270\/63529605\/bbaf270.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,27]],"date-time":"2025-06-27T22:09:39Z","timestamp":1751062179000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bib\/article\/doi\/10.1093\/bib\/bbaf270\/8169587"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5,1]]},"references-count":74,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2025,5,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bib\/bbaf270","relation":{},"ISSN":["1467-5463","1477-4054"],"issn-type":[{"value":"1467-5463","type":"print"},{"value":"1477-4054","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2025,5]]},"published":{"date-parts":[[2025,5,1]]},"article-number":"bbaf270"}}