Agronomic Linked Data (AgroLD): a Knowledge-based System to Enable Integrative Biology in Agronomy
| Autor: | Bertrand Pitollat, Imène Chentli, Pierre Larmande, Clement Jonquet, Valentin Guignon, Nordine El Hassouni, Ndomassi Tando, Gildas Tagny, Aravind Venkatesan, Gaëtan Droc, Mathieu Rouard, Manuel Ruiz |
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| Přispěvatelé: | 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 [France-Sud]), 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), Université de Montpellier (UM)-Institut National de la Recherche Agronomique (INRA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), WEB-CUBE, Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), Institut de Recherche pour le Développement (IRD [France-Sud])-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad) |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Proteomics
Agronomie Computer science Knowledge Bases [SDV.SA.AGRO]Life Sciences [q-bio]/Agricultural sciences/Agronomy Social Sciences ontologie de domaine Ontology (information science) Logiciel Infographics Computer Architecture F30 - Génétique et amélioration des plantes Database and Informatics Methods 0302 clinical medicine Phenomics céréale Psychology Ensembl Génétique Data Management Language 2. Zero hunger 0303 health sciences Gene Ontologies Agriculture Genomics computer.file_format [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM] [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing Knowledge base C30 - Documentation et information Information Retrieval Medicine Recherche de l'information Graphs Functional genomics Biologie Genome Plant Research Article Computer and Information Sciences Science Crops Phenome Research and Analysis Methods 03 medical and health sciences Ontologies Genetics RDF Semantic Web 030304 developmental biology [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB] business.industry Data Visualization [INFO.INFO-WB]Computer Science [cs]/Web Cognitive Psychology Biology and Life Sciences Computational Biology 15. Life on land Genome Analysis Data science Agronomy [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR] Cognitive Science [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM] business computer 030217 neurology & neurosurgery User Interfaces Neuroscience Crop Science Cereal Crops |
| Zdroj: | Plos One 11 (13), . (2018) PLoS ONE PLoS ONE, 2018, 13 (11), pp.e0198270. ⟨10.1371/journal.pone.0198270⟩ PloS One PLoS ONE, Vol 13, Iss 11, p e0198270 (2018) PLoS ONE, Public Library of Science, 2018, 13 (11), pp.e0198270. ⟨10.1371/journal.pone.0198270⟩ |
| ISSN: | 1932-6203 |
| DOI: | 10.1101/325423 |
| Popis: | Exploring the links between genetic and phenotypic traits is an important area of research in agronomy. One of the main objectives of this is to accelerate the development of important traits that can positively impact the agricultural economy. However, due to the existence of complex molecular interactions, to gain complete understanding will warrant data analyses performed at different molecular and environmental levels for a given (plant) subject. For instance, to understand how rice genes involved in metabolism or signaling of growth regulators control the rice panicle architecture. While high-throughput technologies have played a key role in accelerating and generating the much-needed data, these can only partially capture the dynamics in genotypephenotype relations. Consequently, our knowledge of the complex relationships between the different molecular actors responsible for the expression of the phenome in various plant systems remains fragmented. Hence, there is an urgent need to effectively integrate and assimilate complementary information to understand the biological system in its entirety. We have developed AgroLD [1] (www.agrold.org), a knowledge graph system that exploits the Semantic Web technology and FAIR principles [2], to integrate information to integrate data about plant species of high interest for the plant science community e.g., rice, wheat, Arabidopsis and in this way facilitating the formulation of new scientific hypotheses. We present some integration results of the project, which currently focused on genomics, proteomics and phenomics. AgroLD is now an RDF knowledge base of 900M triples created by annotating and integrating more than 100 datasets coming from 15 data sources –such as Ensembl plants [3], Gramene.org [4] and TropGeneDB [5]– with 15 ontologies –such as the Gene Ontology [6] and Plant Ontology [7]. Our objective is to offer a domain specific knowledge platform to solve complex biological and agronomical questions related to the implication of genes 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. |
| Databáze: | OpenAIRE |
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