Study on Quantitative Prediction of Anticancer Compound Activity Based on Neural Network Model

Abstract

Breast cancer poses a serious threat to global women's health. Around this problem, a quantitative prediction model of biological activity based on neural network and a quantitative prediction model of multiple linear regression are established in this paper. 20 kinds of molecular descriptor data with the most significant effect on biological activity of 1974 compounds were selected as input layer and 1 biological activity data as output layer, and a quantitative prediction model of biological activity based on neural network was established. Based on the quantitative prediction model based on parameter setting, the single hidden layer BP neural network structure is used to test the model, and the fitting error R values of the training set and test set of the model are close to 1, and the trend in the scatter diagram is obvious, which shows that the prediction value of the model is more accurate.