{"@context":{"@vocab":"https://cir.nii.ac.jp/schema/1.0/","rdfs":"http://www.w3.org/2000/01/rdf-schema#","dc":"http://purl.org/dc/elements/1.1/","dcterms":"http://purl.org/dc/terms/","foaf":"http://xmlns.com/foaf/0.1/","prism":"http://prismstandard.org/namespaces/basic/2.0/","cinii":"http://ci.nii.ac.jp/ns/1.0/","datacite":"https://schema.datacite.org/meta/kernel-4/","ndl":"http://ndl.go.jp/dcndl/terms/","jpcoar":"https://github.com/JPCOAR/schema/blob/master/2.0/"},"@id":"https://cir.nii.ac.jp/crid/1362262943828539136.json","@type":"Article","productIdentifier":[{"identifier":{"@type":"DOI","@value":"10.1093/nar/gkz232"}},{"identifier":{"@type":"URI","@value":"http://academic.oup.com/nar/article-pdf/47/12/e72/28917064/gkz232.pdf"}}],"dc:title":[{"@value":"An integrative method to predict signalling perturbations for cellular transitions"}],"description":[{"type":"abstract","notation":[{"@value":"<jats:title>Abstract</jats:title><jats:p>Induction of specific cellular transitions is of clinical importance, as it allows to revert disease cellular phenotype, or induce cellular reprogramming and differentiation for regenerative medicine. Signalling is a convenient way to accomplish such transitions without transfer of genetic material. Here we present the first general computational method that systematically predicts signalling molecules, whose perturbations induce desired cellular transitions. This probabilistic method integrates gene regulatory networks (GRNs) with manually-curated signalling pathways obtained from MetaCore from Clarivate Analytics, to model how signalling cues are received and processed in the GRN. The method was applied to 219 cellular transition examples, including cell type transitions, and overall correctly predicted experimentally validated signalling molecules, consistently outperforming other well-established approaches, such as differential gene expression and pathway enrichment analyses. Further, we validated our method predictions in the case of rat cirrhotic liver, and identified the activation of angiopoietins receptor Tie2 as a potential target for reverting the disease phenotype. Experimental results indicated that this perturbation induced desired changes in the gene expression of key TFs involved in fibrosis and angiogenesis. Importantly, this method only requires gene expression data of the initial and desired cell states, and therefore is suited for the discovery of signalling interventions for disease treatments and cellular therapies.</jats:p>"}]}],"creator":[{"@id":"https://cir.nii.ac.jp/crid/1382262943828539008","@type":"Researcher","foaf:name":[{"@value":"Gaia Zaffaroni"}],"jpcoar:affiliationName":[{"@value":"Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette L-4362, Luxembourg"}]},{"@id":"https://cir.nii.ac.jp/crid/1382262943828539137","@type":"Researcher","foaf:name":[{"@value":"Satoshi Okawa"}],"jpcoar:affiliationName":[{"@value":"Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette L-4362, Luxembourg"},{"@value":"Integrated BioBank of Luxembourg, Dudelange L-3555, Luxembourg"}]},{"@id":"https://cir.nii.ac.jp/crid/1382262943828539136","@type":"Researcher","foaf:name":[{"@value":"Manuel Morales-Ruiz"}],"jpcoar:affiliationName":[{"@value":"Biochemistry and Molecular Genetics Department-Hospital Clínic of Barcelona, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona 08036, Spain"},{"@value":"Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Barcelona 08036, Spain"},{"@value":"Working group for the biochemical assessment of hepatic disease-SEQCML, Barcelona 08036, Spain"},{"@value":"Department of Biomedicine-Biochemistry Unit, School of Medicine-University of Barcelona, Barcelona 08036, Spain"}]},{"@id":"https://cir.nii.ac.jp/crid/1382262943828539138","@type":"Researcher","foaf:name":[{"@value":"Antonio del Sol"}],"jpcoar:affiliationName":[{"@value":"Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette L-4362, Luxembourg"},{"@value":"CIC bioGUNE, Bizkaia Technology Park, Derio 48160, Spain"},{"@value":"IKERBASQUE, Basque Foundation for Science, Bilbao 48013, Spain"}]}],"publication":{"publicationIdentifier":[{"@type":"PISSN","@value":"03051048"},{"@type":"EISSN","@value":"13624962"}],"prism:publicationName":[{"@value":"Nucleic Acids Research"}],"dc:publisher":[{"@value":"Oxford University Press (OUP)"}],"prism:publicationDate":"2019-04-05","prism:volume":"47","prism:number":"12","prism:startingPage":"e72","prism:endingPage":"e72"},"reviewed":"false","dc:rights":["http://creativecommons.org/licenses/by/4.0/"],"url":[{"@id":"http://academic.oup.com/nar/article-pdf/47/12/e72/28917064/gkz232.pdf"}],"createdAt":"2019-03-22","modifiedAt":"2024-07-16","relatedProduct":[{"@id":"https://cir.nii.ac.jp/crid/1360849939298579200","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["isReferencedBy"],"jpcoar:relatedTitle":[{"@value":"Inferring the transcriptional regulatory mechanism of signal‐dependent gene expression <i>via</i> an integrative computational approach"}]}],"dataSourceIdentifier":[{"@type":"CROSSREF","@value":"10.1093/nar/gkz232"},{"@type":"CROSSREF","@value":"10.1002/1873-3468.13757_references_DOI_M8FRO7rGBrlsR8RGpIxrjbKYeKD"}]}