在药物发现中应用网络链接预测:文献概述
1Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea.
Expert opinion on drug discovery
|October 5, 2023
概括
药物发现中的链接预测使用网络分析识别新的关系. 解决数据稀疏性和负样本问题是开发可靠的预测工具,成功发现药物的关键.
科学领域:
- 生物医学信息学是生物医学信息学.
- 网络科学 网络科学
- 计算机化药物发现.
背景情况:
- 生物医学网络代表实体之间的关系.
- 链接预测估计了这些网络中的新连接.
- 这对于理解复杂的生物系统和加速药物发现至关重要.
研究的目的:
- 在药物发现中提供网络链路预测的全面概述.
- 总结各种链接预测方法及其应用.
- 讨论在这个领域改善链接预测的挑战和未来方向.
主要方法:
- 基于相似性,基于嵌入和基于概率模型的链接预测方法的审查.
- 讨论处理数据稀疏性和负样本的预处理方法.
- 基于生物医学概念关系的药物发现中的链接预测应用的分析.
主要成果:
- 网络链接预测提供了对生物医学实体关系的整体观点.
- 方法在他们的方法,属性和局限性上有所不同.
- 应用范围包括检测连接模式和预测多实体效应.
结论:
- 链接预测是推断药物发现中新型关系的强大工具.
- 数据稀疏性和缺少负面链接是重大挑战.
- 预处理和增加数据收集可以导致更可靠的链接预测方法用于药物发现.
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