Support vector regression-based QSAR models for prediction of antioxidant activity of phenolic compounds
Abstract The Support vector regression (SVR) was used to investigate quantitative structure–activity relationships (QSAR) of 75 phenolic compounds with Trolox-equivalent antioxidant capacity (TEAC). Geometric structures were optimized at the EF level of the MOPAC software program. Using Pearson corr...
Main Author: | Ying Shi |
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Format: | Article |
Language: | English |
Published: |
Nature Publishing Group
2021-04-01
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Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-021-88341-1 |
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