计算机科学
机器学习
领域(数学)
人工智能
深度学习
药物发现
数据科学
生物信息学
生物
数学
纯数学
作者
Fatemeh Abbasi,Juho Rousu
标识
DOI:10.1016/j.sbi.2024.102827
摘要
In this mini-review, we explore the new prediction methods for drug combination synergy relying on high-throughput combinatorial screens. The fast progress of the field is witnessed in the more than thirty original machine learning methods published since 2021, a clear majority of them based on deep learning techniques. We aim to put these articles under a unifying lens by highlighting the core technologies, the data sources, the input data types and synergy scores used in the methods, as well as the prediction scenarios and evaluation protocols that the articles deal with. Our finding is that the best methods accurately solve the synergy prediction scenarios involving known drugs or cell lines while the scenarios involving new drugs or cell lines still fall short of an accurate prediction level.
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