期刊
FRONTIERS IN GENETICS
卷 13, 期 -, 页码 -出版社
FRONTIERS MEDIA SA
DOI: 10.3389/fgene.2022.961611
关键词
synthetic lethality; gene-gene interaction; machine learning (ML); computational biology; predictive model
Synthetic lethality refers to the interaction of two genes that leads to cell or organism death when both are perturbed, but does not affect viability when only one gene is altered. The exploration of experimental technologies and predictive models in studying synthetic lethal gene pairs contribute to our understanding of cancer biology and the development of cancer therapies.
Synthetic lethality (SL) refers to a genetic interaction in which the simultaneous perturbation of two genes leads to cell or organism death, whereas viability is maintained when only one of the pair is altered. The experimental exploration of these pairs and predictive modeling in computational biology contribute to our understanding of cancer biology and the development of cancer therapies. We extensively reviewed experimental technologies, public data sources, and predictive models in the study of synthetic lethal gene pairs and herein detail biological assumptions, experimental data, statistical models, and computational schemes of various predictive models, speculate regarding their influence on individual sample- and population-based synthetic lethal interactions, discuss the pros and cons of existing SL data and models, and highlight potential research directions in SL discovery.
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