Agronomic Linked Data (AgroLD): A knowledge-based system to enable integrative biology in agronomy
2018
Venkatesan, Aravind | Tagny Ngompe, Gildas | Hassouni, Nordine El | Chentli, Imène | Guignon, Valentin | Jonquet, Clement | Ruiz, Manuel | Larmande, Pierre | Institut de Biologie Computationnelle (IBC) ; Institut National de la Recherche Agronomique (INRA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS) | Amélioration génétique et adaptation des plantes méditerranéennes et tropicales (UMR AGAP) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro) | Bioversity International [Montpellier] ; Bioversity International [Rome] ; Consultative Group on International Agricultural Research [CGIAR] (CGIAR)-Consultative Group on International Agricultural Research [CGIAR] (CGIAR) | WEB Architecture x Semantic WEB x WEB of Data (WEB3) ; Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM) ; Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS) | Diversité, adaptation, développement des plantes (UMR DIADE) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [Occitanie]) | Computational Biology Institute of Montpellier : ANR-11-INBS-0013, IA-11-BINF-0002 ; Institut Francais de Bioinformatique : ANR-11-INBS-0013, IA-11-INBS-0013 ; Labex Agro : ANR-10LABX-001-01, IA-10-LABX-0001 | ANR-11-BINF-0002,IBC,Institut de biologie Computationnelle(2011)
International audience
اظهر المزيد [+] اقل [-]إنجليزي. Recent advances in high-throughput technologies have resulted in a tremendous increase in the amount of omics data produced in plant science. This increase, in conjunction with the heterogeneity and variability of the data, presents a major challenge to adopt an integrative research approach. We are facing an urgent need to effectively integrate and assimilate complementary datasets to understand the biological system as a whole. The Semantic Web offers technologies for the integration of heterogeneous data and their transformation into explicit knowledge thanks to ontologies. We have developed the Agronomic Linked Data (AgroLD-www.agrold.org), a knowledge-based system relying on Semantic Web technologies and exploiting standard domain ontologies, to integrate data about plant species of high interest for the plant science community e.g., rice, wheat, arabidopsis. We present some integration results of the project, which initially focused on genomics, proteomics and phenomics. AgroLD is now an RDF (Resource Description Format) knowledge base of 100M triples created by annotating and integrating more than 50 datasets coming from 10 data sources-such as Gramene.org and TropGeneDB-with 10 ontologies-such as the Gene Ontology and Plant Trait Ontology. Our evaluation results show users appreciate the multiple query modes which support different use cases. AgroLD's objective is to offer a domain specific knowledge platform to solve complex biological and agronomical questions related to the implication of genes/proteins in, for instances, plant disease resistance or high yield traits. We expect the resolution of these questions to facilitate the formulation of new scientific hypotheses to be validated with a knowledge-oriented approach.
اظهر المزيد [+] اقل [-]المعلومات البيبليوغرافية
تم تزويد هذا السجل من قبل Institut national de la recherche agronomique