人类遗传学和基因组学用于药物标识别和优先级:开放标的视角
Ellen M McDonagh1,2,3, Gosia Trynka1,3, Mark McCarthy4
1Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK.
Annual review of biomedical data science
|April 12, 2024
概括
开放目标使用人类遗传学和基因组学数据来识别疾病的潜在药物标. 他们的平台整合了各种证据来优先考虑目标,加速了治疗假设的产生.
科学领域:
- 基因组学和生物信息学
- 药物发现和开发 药物发现和开发
- 人类遗传学 人类遗传学
背景情况:
- 开放目标联盟集成了学术和行业专业知识.
- 利用人类遗传学和基因组学对于理解疾病机制至关重要.
- 有系统的证据整合是有效的目标识别所需的.
研究的目的:
- 概述开放目标方法用于生成治疗假设.
- 突出人类遗传学和基因组学在药物发现中的作用.
- 介绍平台在目标优先设置方面的功能.
主要方法:
- 使用基因至基因机器学习模型,使用来自全基因组关联研究 (GWAS),功能基因组学和表观遗传学的数据.
- 整合多样化的遗传证据,包括基因负担分析,罕见疾病遗传学,人体突变和扰乱分析.
- 采用开源信息平台,系统地建立和评分目标疾病协会.
主要成果:
- 开放目标平台系统地整合了多omics数据,以建立目标疾病关联.
- 一个机器学习模型预测了复杂疾病的潜在药物标.
- 目标属性如临床先行性,可处理性和安全性得分以指导优先级.
结论:
- 人类遗传学和基因组学对于产生强大的治疗假设是非常宝贵的.
- 开放目标平台为目标发现提供了一种动态和系统的方法.
- 这一综合战略加速了对有前途的毒品目标的识别.
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