{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T22:07:13Z","timestamp":1776204433891,"version":"3.50.1"},"reference-count":27,"publisher":"Oxford University Press (OUP)","issue":"11","license":[{"start":{"date-parts":[[2023,11,20]],"date-time":"2023-11-20T00:00:00Z","timestamp":1700438400000},"content-version":"vor","delay-in-days":19,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"German Ministry of Education and Research","award":["01IS18037G"],"award-info":[{"award-number":["01IS18037G"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,11,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>Identifying target promoters of active enhancers is a crucial step for realizing gene regulation and deciphering phenotypes and diseases. Up to now, several computational methods were developed to predict enhancer gene interactions, but they require either many epigenomic and transcriptomic experimental assays to generate cell-type (CT)-specific predictions or a single experiment applied to a large cohort of CTs to extract correlations between activities of regulatory elements. Thus, inferring CT-specific enhancer gene interactions in unstudied or poorly annotated CTs becomes a laborious and costly task.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Here, we aim to infer CT-specific enhancer target interactions, using minimal experimental input. We introduce Cell-specific ENhancer Target pREdiction (CENTRE), a machine learning framework that predicts enhancer target interactions in a CT-specific manner, using only gene expression and ChIP-seq data for three histone modifications for the CT of interest. CENTRE exploits the wealth of available datasets and extracts cell-type agnostic statistics to complement the CT-specific information. CENTRE is thoroughly tested across many datasets and CTs and achieves equivalent or superior performance than existing algorithms that require massive experimental data.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>CENTRE\u2019s open-source code is available at GitHub via https:\/\/github.com\/slrvv\/CENTRE.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btad687","type":"journal-article","created":{"date-parts":[[2023,11,17]],"date-time":"2023-11-17T10:30:23Z","timestamp":1700217023000},"source":"Crossref","is-referenced-by-count":5,"title":["CENTRE: a gradient boosting algorithm for Cell-type-specific ENhancer-Target pREdiction"],"prefix":"10.1093","volume":"39","author":[{"given":"Trisevgeni","family":"Rapakoulia","sequence":"first","affiliation":[{"name":"Max Planck Institute for Molecular Genetics , 14195 Berlin, Germany"}]},{"given":"Sara","family":"Lopez Ruiz De Vargas","sequence":"additional","affiliation":[{"name":"Max Planck Institute for Molecular Genetics , 14195 Berlin, Germany"}]},{"given":"Persia Akbari","family":"Omgba","sequence":"additional","affiliation":[{"name":"Max Planck Institute for Molecular Genetics , 14195 Berlin, Germany"}]},{"given":"Verena","family":"Laupert","sequence":"additional","affiliation":[{"name":"Max Planck Institute for Molecular Genetics , 14195 Berlin, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0555-6561","authenticated-orcid":false,"given":"Igor","family":"Ulitsky","sequence":"additional","affiliation":[{"name":"Max Planck Institute for Molecular Genetics , 14195 Berlin, Germany"},{"name":"Department of Immunology and Regenerative Biology, Weizmann Institute of Science , Rehovot 76100, Israel"},{"name":"Department of Molecular Neuroscience, Weizmann Institute of Science , Rehovot 76100, Israel"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1064-3571","authenticated-orcid":false,"given":"Martin","family":"Vingron","sequence":"additional","affiliation":[{"name":"Max Planck Institute for Molecular Genetics , 14195 Berlin, Germany"}]}],"member":"286","published-online":{"date-parts":[[2023,11,20]]},"reference":[{"key":"2023112311351791900_btad687-B1","doi-asserted-by":"crossref","first-page":"455","DOI":"10.1038\/nature12787","article-title":"An atlas of active enhancers across human cell types and tissues","volume":"507","author":"Andersson","year":"2014","journal-title":"Nature"},{"key":"2023112311351791900_btad687-B2","doi-asserted-by":"crossref","first-page":"1196","DOI":"10.1038\/s41588-019-0434-7","article-title":"Inflated performance measures in enhancer\u2013promoter interaction\u2013prediction methods","volume":"51","author":"Cao","year":"2019","journal-title":"Nat Genet"},{"key":"2023112311351791900_btad687-B3","author":"Chen","year":"2016"},{"key":"2023112311351791900_btad687-B4","doi-asserted-by":"crossref","first-page":"390","DOI":"10.1038\/nrg3454","article-title":"Exploring the three-dimensional organization of genomes: interpreting chromatin interaction data","volume":"14","author":"Dekker","year":"2013","journal-title":"Nat Rev Genet"},{"key":"2023112311351791900_btad687-B5","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1038\/nature11247","article-title":"An integrated encyclopedia of DNA elements in the human genome","volume":"489","author":"ENCODE Project Consortium","year":"2012","journal-title":"Nature"},{"key":"2023112311351791900_btad687-B6","doi-asserted-by":"crossref","first-page":"699","DOI":"10.1038\/s41586-020-2493-4","article-title":"Expanded encyclopaedias of DNA elements in the human and mouse genomes","volume":"583","author":"ENCODE Project Consortium","year":"2020","journal-title":"Nature"},{"key":"2023112311351791900_btad687-B19","first-page":"66","author":"Fisher"},{"key":"2023112311351791900_btad687-B7","doi-asserted-by":"crossref","first-page":"679","DOI":"10.1038\/nmeth.4325","article-title":"Comparison of computational methods for Hi-C data analysis","volume":"14","author":"Forcato","year":"2017","journal-title":"Nat Methods"},{"key":"2023112311351791900_btad687-B8","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1038\/nature08497","article-title":"An oestrogen-receptor-alpha-bound human chromatin interactome","volume":"462","author":"Fullwood","year":"2009","journal-title":"Nature"},{"key":"2023112311351791900_btad687-B9","doi-asserted-by":"crossref","first-page":"1341","DOI":"10.1126\/science.aau0320","article-title":"Developmental enhancers and chromosome topology","volume":"361","author":"Furlong","year":"2018","journal-title":"Science"},{"key":"2023112311351791900_btad687-B10","doi-asserted-by":"crossref","first-page":"996","DOI":"10.1101\/gr.229102","article-title":"The human genome browser at UCSC","volume":"12","author":"Kent","year":"2002","journal-title":"Genome Res"},{"key":"2023112311351791900_btad687-B11","doi-asserted-by":"crossref","first-page":"e1003118","DOI":"10.1371\/journal.pcbi.1003118","article-title":"Software for computing and annotating genomic ranges","volume":"9","author":"Lawrence","year":"2013","journal-title":"PLoS Comput Biol"},{"key":"2023112311351791900_btad687-B12","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1126\/science.1181369","article-title":"Comprehensive mapping of long-range interactions reveals folding principles of the human genome","volume":"326","author":"Lieberman-Aiden","year":"2009","journal-title":"Science"},{"key":"2023112311351791900_btad687-B13","doi-asserted-by":"crossref","first-page":"688","DOI":"10.1016\/j.molcel.2019.12.021","article-title":"Chromosome conformation capture and beyond: toward an integrative view of chromosome structure and function","volume":"77","author":"McCord","year":"2020","journal-title":"Mol Cell"},{"key":"2023112311351791900_btad687-B14","doi-asserted-by":"crossref","first-page":"598","DOI":"10.1038\/ng.3286","article-title":"Mapping long-range promoter contacts in human cells with high-resolution capture Hi-C","volume":"47","author":"Mifsud","year":"2015","journal-title":"Nat Genet"},{"key":"2023112311351791900_btad687-B15","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1186\/s13059-019-1924-8","article-title":"A curated benchmark of enhancer\u2013gene interactions for evaluating enhancer\u2013target gene prediction methods","volume":"21","author":"Moore","year":"2020","journal-title":"Genome Biol"},{"key":"2023112311351791900_btad687-B16","doi-asserted-by":"crossref","first-page":"919","DOI":"10.1038\/nmeth.3999","article-title":"HiChIP: efficient and sensitive analysis of protein-directed genome architecture","volume":"13","author":"Mumbach","year":"2016","journal-title":"Nat Methods"},{"key":"2023112311351791900_btad687-B17","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1186\/s13059-019-1860-7","article-title":"CRUP: a comprehensive framework to predict condition-specific regulatory units","volume":"20","author":"Ramisch","year":"2019","journal-title":"Genome Biol"},{"key":"2023112311351791900_btad687-B18","doi-asserted-by":"crossref","first-page":"777","DOI":"10.1101\/gr.152140.112","article-title":"Patterns of regulatory activity across diverse human cell types predict tissue identity, transcription factor binding, and long-range interactions","volume":"23","author":"Sheffield","year":"2013","journal-title":"Genome Res"},{"key":"2023112311351791900_btad687-B20","doi-asserted-by":"crossref","first-page":"1611","DOI":"10.1016\/j.cell.2015.11.024","article-title":"CTCF-mediated human 3D genome architecture reveals chromatin topology for transcription","volume":"163","author":"Tang","year":"2015","journal-title":"Cell"},{"key":"2023112311351791900_btad687-B21","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1038\/nature11232","article-title":"The accessible chromatin landscape of the human genome","volume":"489","author":"Thurman","year":"2012","journal-title":"Nature"},{"key":"2023112311351791900_btad687-B22","doi-asserted-by":"crossref","first-page":"695","DOI":"10.1016\/j.tcb.2014.07.004","article-title":"In search of the determinants of enhancer\u2013promoter interaction specificity","volume":"24","author":"van Arensbergen","year":"2014","journal-title":"Trends Cell Biol"},{"key":"2023112311351791900_btad687-B23","doi-asserted-by":"crossref","first-page":"854","DOI":"10.1038\/nature07730","article-title":"ChIP-seq accurately predicts tissue-specific activity of enhancers","volume":"457","author":"Visel","year":"2009","journal-title":"Nature"},{"key":"2023112311351791900_btad687-B24","doi-asserted-by":"crossref","first-page":"488","DOI":"10.1038\/ng.3539","article-title":"Enhancer\u2013promoter interactions are encoded by complex genomic signatures on looping chromatin","volume":"48","author":"Whalen","year":"2016","journal-title":"Nat Genet"},{"key":"2023112311351791900_btad687-B25","doi-asserted-by":"crossref","first-page":"11778","DOI":"10.1038\/ncomms11778","article-title":"Improving GENCODE reference gene annotation using a high-stringency proteogenomics workflow","volume":"7","author":"Wright","year":"2016","journal-title":"Nat Commun"},{"key":"2023112311351791900_btad687-B26","doi-asserted-by":"crossref","first-page":"558","DOI":"10.1016\/j.csbj.2020.02.013","article-title":"Exploring 3D chromatin contacts in gene regulation: the evolution of approaches for the identification of functional enhancer\u2013promoter interaction","volume":"18","author":"Xu","year":"2020","journal-title":"Comput Struct Biotechnol J"},{"key":"2023112311351791900_btad687-B27","doi-asserted-by":"crossref","first-page":"750","DOI":"10.1038\/s41467-018-03113-2","article-title":"Enhancing Hi-C data resolution with deep convolutional neural network HiCPlus","volume":"9","author":"Zhang","year":"2018","journal-title":"Nat Commun"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btad687\/53587625\/btad687.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/39\/11\/btad687\/53689313\/btad687.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/39\/11\/btad687\/53689313\/btad687.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,23]],"date-time":"2023-11-23T11:38:47Z","timestamp":1700739527000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/doi\/10.1093\/bioinformatics\/btad687\/7429396"}},"subtitle":[],"editor":[{"given":"Christina","family":"Kendziorski","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2023,11,1]]},"references-count":27,"journal-issue":{"issue":"11","published-print":{"date-parts":[[2023,11,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btad687","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/2023.05.16.541035","asserted-by":"object"}]},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"value":"1367-4803","type":"print"},{"value":"1367-4811","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2023,11,1]]},"published":{"date-parts":[[2023,11,1]]},"article-number":"btad687"}}