AgroLD: a knowledge graph for the plant sciences.

IF 2.5 Q3 GENETICS & HEREDITY
Larmande Pierre, Pittolat Bertrand, Tando Ndomassi, Pomie Yann, Happi Happi Bill Gates, Guignon Valentin, Ruiz Manuel
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引用次数: 0

Abstract

Background: The demand for food is expected to grow substantially in the coming years. To address this challenge, especially in the context of climate change, a deeper understanding of genotype-phenotype relationships is crucial for improving crop yields. Recent advances in high-throughput technologies have transformed the landscape of plant science research. However, there is an urgent need to integrate and consolidate complementary data to understand the biological system.

Results: We introduce AgroLD, a knowledge graph that uses Semantic Web technologies to seamlessly integrate plant science data. AgroLD is designed to facilitate hypothesis formulation and validation within the scientific community. With approximately 1.08 billion triples, it integrates and annotates data from more than 151 datasets across 19 distinct sources.

Conclusion: The overarching goal is to provide a specialized knowledge platform addressing complex biological questions in the plant sciences, including gene participation in plant disease resistance and adaptive responses to climate change.

AgroLD:植物科学知识图谱。
背景:预计未来几年粮食需求将大幅增长。为了应对这一挑战,特别是在气候变化的背景下,更深入地了解基因型-表型关系对于提高作物产量至关重要。高通量技术的最新进展已经改变了植物科学研究的格局。然而,迫切需要整合和巩固互补的数据,以了解生物系统。结果:我们引入了一个名为AgroLD的知识图谱,它使用语义网技术来无缝集成植物科学数据。AgroLD旨在促进科学界的假设制定和验证。它拥有大约10.8亿个三元组,集成并注释了来自19个不同来源的151多个数据集的数据。结论:总体目标是提供一个专业的知识平台,解决植物科学中复杂的生物学问题,包括基因参与植物抗病和对气候变化的适应性反应。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
4.90
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0.00%
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