Automatic selection of molecular descriptors using random forest: Application to drug discovery

作者：

Highlights：

• Random Forest based approach to improve the selection of molecular descriptors.

• Automatic features selection improves drug discovering methods accuracy.

• Reduction of complexity and time requirements allows to explore larger datasets.

摘要

•Random Forest based approach to improve the selection of molecular descriptors.•Automatic features selection improves drug discovering methods accuracy.•Reduction of complexity and time requirements allows to explore larger datasets.

论文关键词：Random forest,Drug discovery,Molecular descriptors,Computational chemistry

论文评审过程：Received 5 July 2016, Revised 5 December 2016, Accepted 6 December 2016, Available online 6 December 2016, Version of Record 22 December 2016.

论文官网地址：https://doi.org/10.1016/j.eswa.2016.12.008