鉴定(生物学)
优先次序
构造(python库)
计算机科学
计算生物学
合成致死
芽殖酵母
生物
基因
遗传学
酿酒酵母
生态学
工程类
DNA修复
程序设计语言
管理科学
作者
Lucile M. Jeusset,Kirk J. McManus
出处
期刊:Methods in molecular biology
日期:2021-01-01
卷期号:: 115-133
被引量:1
标识
DOI:10.1007/978-1-0716-1740-3_6
摘要
Characterizing genetic interactions in humans, including synthetic lethal interactions, can provide fundamental insight into protein functions and pathway interactions. However, it can also assist in the development of innovative therapeutic strategies by uncovering novel drug targets used to combat diseases like cancer. To expedite the discovery of novel synthetic lethal interactions in humans, cross-species candidate gene approaches rely on the evolutionary conservation of genetic interactions between organisms. Here, we provide a guide that couples bioinformatic approaches and publicly available datasets from model organisms with cross-species approaches to expedite the identification of candidate synthetic lethal interactions to test in humans. First, we detail a method to identify relevant genetic interactions in budding yeast and subsequently provide a prioritization scheme to identify the most promising yeast interactions to pursue. Finally, we provide details on the tools and approaches used to identify the corresponding human orthologs to ultimately generate a testable network of candidate human synthetic lethal interactions. In summary, this approach leverages publicly available resources and datasets to expedite the identification of conserved synthetic lethal interactions in humans.
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