通过人工智能赋予自然产品科学权力:利用多式联网数据和知识图
David Meijer1, Mehdi A Beniddir2, Connor W Coley3
1Bioinformatics Group, Wageningen University & Research, Droevendaalsesteeg 1, 6708 PB, Wageningen, the Netherlands. justin.vanderhooft@wur.nl.
Natural product reports
|August 16, 2024
概括
人工智能 (AI) 可以通过克服数据挑战来推动自然产品研究. 创建知识图将使人工智能模型能够模仿该领域的专家决策.
科学领域:
- 自然产品研究自然产品研究
- 化学信息学 化学信息学
- 科学中的人工智能.
背景情况:
- 人工智能 (AI) 正在改变跨学科的科学发现.
- 人工智能在天然产品研究中的应用由于数据挑战而受到限制.
- 现有的天然产品数据是多式联运的,不平衡的,不标准化的,在存储库中分散的.
研究的目的:
- 解决人工智能在天然产品研究中的应用局限性.
- 支持民主化自然产品数据的倡议.
- 为开发先进的人工智能模型提出知识图方法.
主要方法:
- 确定天然产品数据可访问性和标准化方面的挑战.
- 倡导创建一个全面的天然产品知识图表.
- 探索知识图的潜力,以整合不同的数据类型.
主要成果:
- 自然产品数据的现状阻碍了人工智能模型的发展.
- 一个知识图可以统一分散和异质的自然产品数据.
- 在知识图上训练的AI模型可以模拟人类的认知过程.
结论:
- 统一的知识图对于释放人工智能在自然产品科学中的潜力至关重要.
- 通过知识图表来民主化自然产品数据将加速发现.
- 未来的人工智能模型可以通过改进的数据基础设施模仿自然产品科学家的决策.
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