基于人工神经网络和遗传算法的雷帕霉素发酵培养基优化  

Optimization of Rapamycin Fermentation Medium Based on Artificial Neural Network and Genetic Algorithm

作　　者：陈晓明[1] 金东伟[1] 陈夏琴[1] CHEN Xiao-ming;JIN Dong-wei;CHEN Xia-qin(Fujian Institute of Microbiology,Fuzhou 350007,China)

机构地区：[1]福建省微生物研究所,福建福州350007

出　　处：《海峡药学》2025年第1期13-17,共5页Strait Pharmaceutical Journal

基　　金：福建省公益类科研院所专项(2021R1005004)。

摘　　要：目的采用人工神经网络和遗传算法相结合,优化雷帕霉素发酵培养基。方法首先通过Plackett-Burman设计实验,筛选影响雷帕霉素产量显著因素;再采用Box-Behnken实验建立数据样本训练人工神经网络模型,最后耦合遗传算法对模型全局寻优。结果黄豆饼粉和赖氨酸对雷帕霉素的合成有显著的正效应,葡萄糖对雷帕霉素的合成具有显著的负效应。遗传算法-人工神经网络的决定系数与相对误差分别为0.998与2.29%。最终获得影响雷帕霉素发酵主要因素配比:葡萄糖6.5 g·L^(-1),黄豆饼粉23.2 g·L^(-1),赖氨酸7.9 g·L^(-1)。结论优化后培养基的发酵水平较原培养基提高了21.1%,达到预期效果。OBJECTIVE Using a combination of artificial neural networks and genetic algorithms to optimize the rapamycin fermentation medium.METHODS Firstly,Plackett Burman designed experiments to screen for significant factors affecting the production of rapamycin;Then,the Box Behnken experiment is used to establish a data sample to train an artificial neural network model,and finally,a genetic algorithm is coupled to a global optimize the model.RESULTS Soybean cake powder and lysine have a significant positive effect on the synthesis of rapamycin,while glucose has a significant negative effect on the synthesis of rapamycin.The determination coefficient and relative error of the genetic algorithm artificial neural network are 0.998 and 2.29%,respectively.Finally,the main factors affecting the fermentation of rapamycin were determined as follows:glucose 6.5 g·L^(-1),soybean cake powder 23.2 g·L^(-1),and lysine 7.9 g·L^(-1).CONCLUSION The fermentation level of the optimized culture medium increased by 21.1%compared to the original culture medium,achieving the expected effect.

关 键 词：人工神经网络 遗传算法 雷帕霉素 优化 

分 类 号：R927[医药卫生—药学]