药物发现
业务流程发现
化学空间
计算机科学
天然产物
过程(计算)
计算生物学
生化工程
数据科学
人工智能
机器学习
生物
生物信息学
工程类
在制品
生物化学
运营管理
业务流程建模
操作系统
业务流程
作者
Autumn Arnold,Jeremie Alexander,Gary Liu,Jonathan Stokes
标识
DOI:10.1080/17460441.2023.2251400
摘要
Despite the important role that microbial NPs play in the development of novel drugs, their discovery has declined due to challenges associated with the conventional discovery process. ML is positioned to overcome these limitations given its ability to model complex datasets and generalize to novel chemical and sequence space. Unsurprisingly, ML comes with its own limitations that must be considered for its successful implementation. The authors stress the importance of continuing to build high quality and open access NP datasets to further increase the utility of ML in NP discovery.
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