Multi-target QSAR modelling of chemo-genomic data analysis based on Extreme Learning Machine
作者：
Highlights：
• QSAR model applied for activity prediction of novel drugs and validated by docking.
• QSAR model based on Extreme Learning Machine for (PXC 50) is presented.
• ELM proved less training time consumed and it gives high prediction performance.
• The GBWOA-ELM aims to improve the WOA by using Genetic Algorithm.
• The results show that the (GBWOA-ELM) model is accurate to predict the PXC50.
摘要
•QSAR model applied for activity prediction of novel drugs and validated by docking.•QSAR model based on Extreme Learning Machine for (PXC 50) is presented.•ELM proved less training time consumed and it gives high prediction performance.•The GBWOA-ELM aims to improve the WOA by using Genetic Algorithm.•The results show that the (GBWOA-ELM) model is accurate to predict the PXC50.
论文关键词：Machine learning,Whale Optimization Algorithm,Genetic algorithm,Extreme learning machine,QSAR,Molecular docking,ExCAPE chemo-genomics database
论文评审过程：Received 24 March 2019, Revised 27 July 2019, Accepted 19 August 2019, Available online 29 August 2019, Version of Record 20 January 2020.
论文官网地址：https://doi.org/10.1016/j.knosys.2019.104977
