- 作者: 劉樹深
- 作者服務機構: College of Bioengineering, Chongqing University, Chongqing 400044, P. R. China
- 中文摘要: The molecular holographic distance vector (MHDV) is employed to characterize the structures of 51 substituted benzenes. 29 descriptors from 91 MHDV ones have nonzero values where 3 descriptors have only one nonzero sample and 1 descriptor only two nonzero samples. A genetic algorithm is used to select an optimal combination of the variables from the remaining 25 nonzero descriptors. Then the optimal descriptors are employed to relate to the relative biodegradability using multiple linear regression method. The 6-variable linear model developed has high quality where the correlation coefficient of estimations and the root mean square error of estimations are 0.9604 and 0.280, respectively, and the correlation coefficient of predictions and the root mean square error of predictions for leave-one-out procedure are 0.9471 and 0.324, respectively.
- 英文摘要: --
- 中文關鍵字: Molecular Holographic Distance Vector (MHDV); Genetic Algorithm (GA); Quantitative Structure-Biodegradability Relationship (QSBR); Biodegradability; Substituted benzenes; Multiple Linear Regression (MLR).
- 英文關鍵字: Molecular Holographic Distance Vector (MHDV); Genetic Algorithm (GA); Quantitative Structure-Biodegradability Relationship (QSBR); Biodegradability; Substituted benzenes; Multiple Linear Regression (MLR).