王泽;李新城;朱伟兴. 药物生物利用度遗传神经网络预测研究J. 药学学报, 2006,41(12): 1180-1183.
引用本文: 王泽;李新城;朱伟兴. 药物生物利用度遗传神经网络预测研究J. 药学学报, 2006,41(12): 1180-1183.
WANG Ze ; LI Xin-cheng; ZHU Wei-xin. Prediction of drug bioavailability by genetic algorithm and artificial neural networkJ. Acta Pharmaceutica Sinica, 2006,41(12): 1180-1183.
Citation: WANG Ze ; LI Xin-cheng; ZHU Wei-xin. Prediction of drug bioavailability by genetic algorithm and artificial neural networkJ. Acta Pharmaceutica Sinica, 2006,41(12): 1180-1183.

药物生物利用度遗传神经网络预测研究

Prediction of drug bioavailability by genetic algorithm and artificial neural network

  • 摘要: 目的对药物生物利用度进行遗传神经网络预测。方法将人工神经网络与遗传算法应用于药物生物利用度预测研究,提出了采用遗传算法对人工神经网络进行优化的网络模型建立方法,利用遗传算法对神经网络模型中的权重进行优化,同时运用遗传算法强大的搜寻功能,得到特定条件下模型的最优解。并以药物分子体积(V)、分子折射率(R)、脂水分配系数(lgPC)、水合能(H)、分子极化度(P)、前线轨道能量EHOMO和EHOMO为网络输入参数,以药物的平均生物利用度为网络输出参数,建立了药物生物利用度遗传神经网络预测模型。结果经遗传算法优化的GA-BP神经网络模型对生物利用度的预测精度为95.9%。结论该模型可以用于药物生物利用度预测研究。

     

    Abstract: AimTo set up an artificial neural network system and optimize by genetic algorithm (GA) to predict drug bioavailability. MethodsGenetic algorithm was used to optimize weights of the artificial neural network. The optimal solution of the artificial neural network model at a specific condition was obtained using the good search ability of genetic algorithm in order to predict drug bioavailability. Volume, refractivity, lgPC, hydration, polarizability, EHOMO and ELUMO are inputs of the drug bioavailability prediction neural network, and its output is average drug bioavailability. ResultsThe prediction precision of average drug bioavailability of the GA- neural network model is 95.9%. ConclusionThis model can be used in the forecasting of drug bioavailability.

     

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