{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T22:06:21Z","timestamp":1774476381049,"version":"3.50.1"},"reference-count":8,"publisher":"Oxford University Press (OUP)","issue":"12","license":[{"start":{"date-parts":[[2018,11,15]],"date-time":"2018-11-15T00:00:00Z","timestamp":1542240000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"name":"IMEC Strategic Funding"},{"name":"IWT Exaptation"},{"name":"FWO 06260"},{"DOI":"10.13039\/501100007229","name":"Special Research Fund","doi-asserted-by":"crossref","award":["PF\/10\/016"],"award-info":[{"award-number":["PF\/10\/016"]}],"id":[{"id":"10.13039\/501100007229","id-type":"DOI","asserted-by":"crossref"}]},{"name":"ERC Consolidator","award":["724226_cis-CONTROL"],"award-info":[{"award-number":["724226_cis-CONTROL"]}]},{"DOI":"10.13039\/501100013845","name":"Foundation Against Cancer","doi-asserted-by":"crossref","award":["2016-070"],"award-info":[{"award-number":["2016-070"]}],"id":[{"id":"10.13039\/501100013845","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,6,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Summary<\/jats:title>\n                  <jats:p>Inferring a Gene Regulatory Network (GRN) from gene expression data is a computationally expensive task, exacerbated by increasing data sizes due to advances in high-throughput gene profiling technology, such as single-cell RNA-seq. To equip researchers with a toolset to infer GRNs from large expression datasets, we propose GRNBoost2 and the Arboreto framework. GRNBoost2 is an efficient algorithm for regulatory network inference using gradient boosting, based on the GENIE3 architecture. Arboreto is a computational framework that scales up GRN inference algorithms complying with this architecture. Arboreto includes both GRNBoost2 and an improved implementation of GENIE3, as a user-friendly open source Python package.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>Arboreto is available under the 3-Clause BSD license at http:\/\/arboreto.readthedocs.io.<\/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\/bty916","type":"journal-article","created":{"date-parts":[[2018,11,14]],"date-time":"2018-11-14T12:12:43Z","timestamp":1542197563000},"page":"2159-2161","source":"Crossref","is-referenced-by-count":543,"title":["GRNBoost2 and Arboreto: efficient and scalable inference of gene regulatory networks"],"prefix":"10.1093","volume":"35","author":[{"given":"Thomas","family":"Moerman","sequence":"first","affiliation":[{"name":"KU Leuven ESAT\/STADIUS, VDA-lab"},{"name":"IMEC Smart Applications and Innovation Services"}]},{"given":"Sara","family":"Aibar Santos","sequence":"additional","affiliation":[{"name":"Laboratory of Computational Biology, VIB Center for Brain & Disease Research"},{"name":"Department of Human Genetics, KU Leuven, Leuven, Belgium"}]},{"given":"Carmen","family":"Bravo Gonz\u00e1lez-Blas","sequence":"additional","affiliation":[{"name":"Laboratory of Computational Biology, VIB Center for Brain & Disease Research"},{"name":"Department of Human Genetics, KU Leuven, Leuven, Belgium"}]},{"given":"Jaak","family":"Simm","sequence":"additional","affiliation":[{"name":"IMEC Smart Applications and Innovation Services"},{"name":"KU Leuven ESAT\/STADIUS, Bioinformatics Lab"}]},{"given":"Yves","family":"Moreau","sequence":"additional","affiliation":[{"name":"IMEC Smart Applications and Innovation Services"},{"name":"KU Leuven ESAT\/STADIUS, Bioinformatics Lab"}]},{"given":"Jan","family":"Aerts","sequence":"additional","affiliation":[{"name":"KU Leuven ESAT\/STADIUS, VDA-lab"},{"name":"IMEC Smart Applications and Innovation Services"}]},{"given":"Stein","family":"Aerts","sequence":"additional","affiliation":[{"name":"Laboratory of Computational Biology, VIB Center for Brain & Disease Research"},{"name":"Department of Human Genetics, KU Leuven, Leuven, Belgium"}]}],"member":"286","published-online":{"date-parts":[[2018,11,15]]},"reference":[{"key":"2023012713221161300_bty916-B1","doi-asserted-by":"crossref","first-page":"1083","DOI":"10.1038\/nmeth.4463","article-title":"SCENIC: single-cell regulatory network inference and clustering","volume":"14","author":"Aibar","year":"2017","journal-title":"Nat. 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