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Agronomic Linked Data (AgroLD): A knowledge-based system to enable integrative biology in agronomy
by
Jonquet, Clement
, Larmande, Pierre
, Guignon, Valentin
, Venkatesan, Aravind
, Chentli, Imene
, Ruiz, Manuel
, Hassouni, Nordine El
, Tagny Ngompe, Gildas
in
Acids
/ Agricultural sciences
/ Agriculture
/ Agronomy
/ Arabidopsis
/ Arabidopsis thaliana
/ Bioinformatics
/ Biology
/ Biology and Life Sciences
/ Computer and Information Sciences
/ Computer Science
/ Consortia
/ Datasets
/ Disease resistance
/ Document and Text Processing
/ Explicit knowledge
/ Genes
/ Genetic transformation
/ Genome, Plant
/ Genomics
/ Heterogeneity
/ High-throughput screening (Biochemical assaying)
/ Information Retrieval
/ Integration
/ Knowledge based systems
/ Knowledge Bases
/ Knowledge bases (artificial intelligence)
/ Knowledge management
/ Life Sciences
/ Linked Data
/ Molecular biology
/ Ontology
/ Plant communities
/ Plant diseases
/ Plant genetics
/ Plant immunity
/ Plant sciences
/ Plant species
/ Proteins
/ Proteomics
/ Quantitative Methods
/ Research and Analysis Methods
/ Rice
/ Semantic web
/ Semantics
/ Social Sciences
/ Technology
/ Technology application
/ Transformation
/ Usability
/ Web
/ Web site management software
/ Wheat
2018
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Agronomic Linked Data (AgroLD): A knowledge-based system to enable integrative biology in agronomy
by
Jonquet, Clement
, Larmande, Pierre
, Guignon, Valentin
, Venkatesan, Aravind
, Chentli, Imene
, Ruiz, Manuel
, Hassouni, Nordine El
, Tagny Ngompe, Gildas
in
Acids
/ Agricultural sciences
/ Agriculture
/ Agronomy
/ Arabidopsis
/ Arabidopsis thaliana
/ Bioinformatics
/ Biology
/ Biology and Life Sciences
/ Computer and Information Sciences
/ Computer Science
/ Consortia
/ Datasets
/ Disease resistance
/ Document and Text Processing
/ Explicit knowledge
/ Genes
/ Genetic transformation
/ Genome, Plant
/ Genomics
/ Heterogeneity
/ High-throughput screening (Biochemical assaying)
/ Information Retrieval
/ Integration
/ Knowledge based systems
/ Knowledge Bases
/ Knowledge bases (artificial intelligence)
/ Knowledge management
/ Life Sciences
/ Linked Data
/ Molecular biology
/ Ontology
/ Plant communities
/ Plant diseases
/ Plant genetics
/ Plant immunity
/ Plant sciences
/ Plant species
/ Proteins
/ Proteomics
/ Quantitative Methods
/ Research and Analysis Methods
/ Rice
/ Semantic web
/ Semantics
/ Social Sciences
/ Technology
/ Technology application
/ Transformation
/ Usability
/ Web
/ Web site management software
/ Wheat
2018
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Agronomic Linked Data (AgroLD): A knowledge-based system to enable integrative biology in agronomy
by
Jonquet, Clement
, Larmande, Pierre
, Guignon, Valentin
, Venkatesan, Aravind
, Chentli, Imene
, Ruiz, Manuel
, Hassouni, Nordine El
, Tagny Ngompe, Gildas
in
Acids
/ Agricultural sciences
/ Agriculture
/ Agronomy
/ Arabidopsis
/ Arabidopsis thaliana
/ Bioinformatics
/ Biology
/ Biology and Life Sciences
/ Computer and Information Sciences
/ Computer Science
/ Consortia
/ Datasets
/ Disease resistance
/ Document and Text Processing
/ Explicit knowledge
/ Genes
/ Genetic transformation
/ Genome, Plant
/ Genomics
/ Heterogeneity
/ High-throughput screening (Biochemical assaying)
/ Information Retrieval
/ Integration
/ Knowledge based systems
/ Knowledge Bases
/ Knowledge bases (artificial intelligence)
/ Knowledge management
/ Life Sciences
/ Linked Data
/ Molecular biology
/ Ontology
/ Plant communities
/ Plant diseases
/ Plant genetics
/ Plant immunity
/ Plant sciences
/ Plant species
/ Proteins
/ Proteomics
/ Quantitative Methods
/ Research and Analysis Methods
/ Rice
/ Semantic web
/ Semantics
/ Social Sciences
/ Technology
/ Technology application
/ Transformation
/ Usability
/ Web
/ Web site management software
/ Wheat
2018
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Agronomic Linked Data (AgroLD): A knowledge-based system to enable integrative biology in agronomy
Journal Article
Agronomic Linked Data (AgroLD): A knowledge-based system to enable integrative biology in agronomy
2018
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Overview
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.
Publisher
Public Library of Science,Public Library of Science (PLoS)
Subject
/ Agronomy
/ Biology
/ Computer and Information Sciences
/ Datasets
/ Document and Text Processing
/ Genes
/ Genomics
/ High-throughput screening (Biochemical assaying)
/ Knowledge bases (artificial intelligence)
/ Ontology
/ Proteins
/ Research and Analysis Methods
/ Rice
/ Web
/ Web site management software
/ Wheat
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