{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T11:49:51Z","timestamp":1753876191346,"version":"3.41.2"},"reference-count":29,"publisher":"Oxford University Press (OUP)","license":[{"start":{"date-parts":[[2021,1,18]],"date-time":"2021-01-18T00:00:00Z","timestamp":1610928000000},"content-version":"vor","delay-in-days":17,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"SyMeTRIC Connect Talent project"},{"name":"National Research Agency","award":["ANR-10-BTBR-02-04-11."],"award-info":[{"award-number":["ANR-10-BTBR-02-04-11."]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,1,18]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Huge efforts are currently underway to address the organization of biological knowledge through linked open databases. These databases can be automatically queried to reconstruct regulatory and signaling networks. However, assembling networks implies manual operations due to source-specific identification of biological entities and relationships, multiple life-science databases with redundant information and the difficulty of recovering logical flows in biological pathways. We propose a framework based on Semantic Web technologies to automate the reconstruction of large-scale regulatory and signaling networks in the context of tumor cells modeling and drug screening. The proposed tool is pyBRAvo (python Biological netwoRk Assembly), and here we have applied it to a dataset of 910 gene expression measurements issued from liver cancer patients. The tool is publicly available at https:\/\/github.com\/pyBRAvo\/pyBRAvo.<\/jats:p>","DOI":"10.1093\/database\/baaa113","type":"journal-article","created":{"date-parts":[[2020,12,12]],"date-time":"2020-12-12T06:04:13Z","timestamp":1607753053000},"source":"Crossref","is-referenced-by-count":4,"title":["Large-scale regulatory and signaling network assembly through linked open data"],"prefix":"10.1093","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3093-5873","authenticated-orcid":false,"given":"M","family":"Lefebvre","sequence":"first","affiliation":[{"name":"UMR 1332 Biologie du Fruit et Pathologie, INRAE, Univ. Bordeaux, 72 Avenue Edouard Bourlaux, CS20032, 33882, Villenave d\u2019Ornon cedex, France"}]},{"given":"A","family":"Gaignard","sequence":"additional","affiliation":[{"name":"Universit\u00e9 de Nantes, CNRS, INSERM, l\u2019Institut du Thorax F-44000, Nantes, France"}]},{"given":"M","family":"Folschette","sequence":"additional","affiliation":[{"name":"Univ. Lille, CNRS, Centrale Lille, UMR 9189 - CRIStAL - Centre de Recherche en Informatique Signal et Automatique de Lille, F-59000 Lille, France"}]},{"given":"J","family":"Bourdon","sequence":"additional","affiliation":[{"name":"Universit\u00e9 de Nantes, Centrale Nantes, CNRS, UMR 6004 - LS2N - Laboratoire des Sciences du Num\u00e9rique de Nantes, F-44000 Nantes, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5192-0745","authenticated-orcid":false,"given":"C","family":"Guziolowski","sequence":"additional","affiliation":[{"name":"Universit\u00e9 de Nantes, Centrale Nantes, CNRS, UMR 6004 - LS2N - Laboratoire des Sciences du Num\u00e9rique de Nantes, F-44000 Nantes, France"}]}],"member":"286","published-online":{"date-parts":[[2021,1,18]]},"reference":[{"key":"2021011808051547800_R1","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1038\/nature01254","article-title":"Computational systems biology","volume":"420","author":"Kitano","year":"2002","journal-title":"Nature"},{"key":"2021011808051547800_R2","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1007\/s12035-013-8489-4","article-title":"Integrating pathways of Parkinson\u2019s disease in a molecular interaction map","volume":"49","author":"Fujita","year":"2014","journal-title":"Mol. 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