关于计算药物重新利用的OREGANO知识图
Marina Boudin1, Gayo Diallo2, Martin Drancé2
1AHeaD team, Bordeaux Population Health Inserm U1219, Univ. Bordeaux, F-33000, Bordeaux, France. marina.boudin@u-bordeaux.fr.
Scientific data
|December 6, 2023
概括
奥里加诺知识图为计算药物重新定位提供了一个免费可用的资源. 它整合了各种药物和天然化合物数据,通过链接预测加速药物发现.
科学领域:
- 计算生物学是一种计算生物学.
- 药理学 药理学是指药理学的学科.
- 生物信息学是一种生物信息学.
背景情况:
- 与传统方法相比,药物重新定位加速了药物发现.
- 使用知识图的计算方法显示出产生药物标假设的前景.
- 缺乏一个全面的,社区可访问的知识图,整合广泛的药物特征.
研究的目的:
- 介绍OREGANO知识图,这是一个用于药物重新定位的新型资源.
- 将自然化合物数据纳入一个全面的知识图.
- 提供对知识图及其相关ETL源代码的开放访问.
主要方法:
- 通过整合来自多个来源的数据,从头开始开发了一个知识图.
- 为数据集成设计了一个图形模型和一个节点合并策略.
- 实现了一个提取,转换,加载 (ETL) 过程与数据清理.
主要成果:
- 成功构建了OREGANO知识图,包括自然化合物数据.
- 知识图和ETL源代码在GitHub上公开提供.
- 该资源通过链接预测促进了对药物重新定位的假设生成.
结论:
- 奥里加诺解决了对药物重新定位的整体,社区可访问的知识图的需求.
- 集成的数据和OREGANO的开源性质可以推动计算药物发现.
- 该资源支持更快,更实惠的药物开发管道.
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