Title :

Large-scale regulatory and signaling network assembly through linked open data

Author(s) :

Lefebvre, Marie [Auteur]
Biologie du fruit et pathologie [BFP]
Gaignard, Alban [Auteur]
Unité de recherche de l'institut du thorax [ITX-lab]
Folschette, Maxime [Auteur]
Centrale Lille
BioComputing
Bourdon, Jérémie [Auteur]
Laboratoire des Sciences du Numérique de Nantes [LS2N]
Combinatoire et Bioinformatique [LS2N - équipe COMBI]
Guziolowski, Carito [Auteur]
Laboratoire des Sciences du Numérique de Nantes [LS2N]
École Centrale de Nantes [ECN]
Combinatoire et Bioinformatique [LS2N - équipe COMBI]

Journal title :

Database - The journal of Biological Databases and Curation

Pages :

baaa113

Publisher :

Oxford University Press

Publication date :

2021

ISSN :

1758-0463

HAL domain(s) :

Informatique [cs]/Bio-informatique [q-bio.QM]
Sciences du Vivant [q-bio]/Bio-Informatique, Biologie Systémique [q-bio.QM]
Informatique [cs]/Modélisation et simulation
Informatique [cs]/Base de données [cs.DB]
Sciences du Vivant [q-bio]

English abstract : [en]

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, ...
Show more >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 sourcespecific 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 largescale 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/pyBRAvoShow less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

ANR Project :

BIOelectrosynthèse pour le Raffinage des déchets Residuels

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL