{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,23]],"date-time":"2026-04-23T03:59:27Z","timestamp":1776916767002,"version":"3.51.2"},"reference-count":49,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2021,9,9]],"date-time":"2021-09-09T00:00:00Z","timestamp":1631145600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"name":"Ministry of Universities and Research"},{"name":"Big Data Analytics","award":["AIM 1852414-1"],"award-info":[{"award-number":["AIM 1852414-1"]}]},{"name":"UKRI Research England\u2019s THYME"},{"name":"Children\u2019s Liver Disease Foundation Research"},{"name":"Apulia Region through the \u2018Research for Innovation\u2014REFIN\u2019","award":["7EDD092A"],"award-info":[{"award-number":["7EDD092A"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,1,3]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Motivation<\/jats:title><jats:p>Gene regulation is responsible for controlling numerous physiological functions and dynamically responding to environmental fluctuations. Reconstructing the human network of gene regulatory interactions is thus paramount to understanding the cell functional organization across cell types, as well as to elucidating pathogenic processes and identifying molecular drug targets. Although significant effort has been devoted towards this direction, existing computational methods mainly rely on gene expression levels, possibly ignoring the information conveyed by mechanistic biochemical knowledge. Moreover, except for a few recent attempts, most of the existing approaches only consider the information of the organism under analysis, without exploiting the information of related model organisms.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>We propose a novel method for the reconstruction of the human gene regulatory network, based on a transfer learning strategy that synergically exploits information from human and mouse, conveyed by gene-related metabolic features generated in silico from gene expression data. Specifically, we learn a predictive model from metabolic activity inferred via tissue-specific metabolic modelling of artificial gene knockouts. Our experiments show that the combination of our transfer learning approach with the constructed metabolic features provides a significant advantage in terms of reconstruction accuracy, as well as additional clues on the contribution of each constructed metabolic feature.<\/jats:p><\/jats:sec><jats:sec><jats:title>Availability and implementation<\/jats:title><jats:p>The method, the datasets and all the results obtained in this study are available at: https:\/\/doi.org\/10.6084\/m9.figshare.c.5237687.<\/jats:p><\/jats:sec><jats:sec><jats:title>Supplementary information<\/jats:title><jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bioinformatics\/btab647","type":"journal-article","created":{"date-parts":[[2021,9,8]],"date-time":"2021-09-08T11:46:10Z","timestamp":1631101570000},"page":"487-493","source":"Crossref","is-referenced-by-count":40,"title":["Integrating genome-scale metabolic modelling and transfer learning for human gene regulatory network reconstruction"],"prefix":"10.1093","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2520-3616","authenticated-orcid":false,"given":"Gianvito","family":"Pio","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of Bari Aldo Moro , Bari 70125, Italy"},{"name":"Big Data Lab, National Interuniversity Consortium for Informatics (CINI) , Rome 00185, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8641-7880","authenticated-orcid":false,"given":"Paolo","family":"Mignone","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Bari Aldo Moro , Bari 70125, Italy"},{"name":"Big Data Lab, National Interuniversity Consortium for Informatics (CINI) , Rome 00185, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Giuseppe","family":"Magazz\u00f9","sequence":"additional","affiliation":[{"name":"School of Computing, Engineering & Digital Technologies, Teesside University , Tees Valley TS1 3BA, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4518-5913","authenticated-orcid":false,"given":"Guido","family":"Zampieri","sequence":"additional","affiliation":[{"name":"School of Computing, Engineering & Digital Technologies, Teesside University , Tees Valley TS1 3BA, UK"},{"name":"Department of Biology, University of Padova , Padova 35121, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6690-7583","authenticated-orcid":false,"given":"Michelangelo","family":"Ceci","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Bari Aldo Moro , Bari 70125, Italy"},{"name":"Big Data Lab, National Interuniversity Consortium for Informatics (CINI) , Rome 00185, Italy"},{"name":"Department of Knowledge Technologies, Jozef Stefan Institute , Ljubljana 1000, Slovenia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3140-7909","authenticated-orcid":false,"given":"Claudio","family":"Angione","sequence":"additional","affiliation":[{"name":"School of Computing, Engineering & Digital Technologies, Teesside University , Tees Valley TS1 3BA, UK"},{"name":"Centre for Digital Innovation, Teesside University, Campus Heart , Tees Valley TS1 3BX, UK"},{"name":"Healthcare Innovation Centre, Teesside University, Campus Heart , Tees Valley TS1 3BX, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2021,9,9]]},"reference":[{"key":"2023020108445572600_btab647-B1","doi-asserted-by":"crossref","first-page":"e1007100","DOI":"10.1371\/journal.pcbi.1007100","article-title":"Predicting gastrointestinal drug effects using contextualized metabolic models","volume":"15","author":"Ben Guebila","year":"2019","journal-title":"PLoS Comput. 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