[A prediction model for the activity of insecticidal crystal proteins from Bacillus thuringiensis based on support vector machine].
A quantitative structure-property relationship (QSPR) model in terms of amino acid composition and the activity of Bacillus thuringiensis insecticidal crystal proteins was established. Support vector machine (SVM) is a novel general machine-learning tool based on the structural risk minimization principle that exhibits good generalization when fault samples are few; it is especially suitable for classification, forecasting, and estimation in cases where small amounts of samples are involved such as fault diagnosis; however, some parameters of SVM are selected based on the experience of the operator, which has led to decreased efficiency of SVM in practical application. The uniform design (UD) method was applied to optimize the running parameters of SVM. It was found that the average accuracy rate approached 73% when the penalty factor was 0.01, the epsilon 0.2, the gamma 0.05, and the range 0.5. The results indicated that UD might be used an effective method to optimize the parameters of SVM and SVM and could be used as an alternative powerful modeling tool for QSPR studies of the activity of Bacillus thuringiensis (Bt) insecticidal crystal proteins. Therefore, a novel method for predicting the insecticidal activity of Bt insecticidal crystal proteins was proposed by the authors of this study.
Lin
Yi
Y
Department of Bioengineering & Biotechnology , Huaqiao University, Key Laboratory of Industrial Biotechnology of Fujian Province Universities, Quanzhou 362021, China. lyhxm@hqu.edu.cn
Cai
Fu-Ying
FY
Zhang
Guang-Ya
GY
D000465:Algorithms; D000596:Amino Acids / Q000235:genetics; D000818:Animals; D001185:Artificial Intelligence; D000083722:Bacillus thuringiensis Toxins; D001426:Bacterial Proteins / Q000145:classification / Q000235:genetics / Q000633:toxicity*; D002470:Cell Survival / Q000187:drug effects; D001517:Coleoptera / Q000254:growth & development; D004175:Diptera / Q000254:growth & development; D004731:Endotoxins / Q000145:classification / Q000235:genetics / Q000633:toxicity*; D006460:Hemolysin Proteins / Q000145:classification / Q000235:genetics / Q000633:toxicity*; D007300:Insect Control / Q000379:methods / Q000706:statistics & numerical data; D007306:Insecticides / Q000633:toxicity; D007915:Lepidoptera / Q000254:growth & development; D008954:Models, Biological; D015203:Reproducibility of Results; D018675:Toxicity Tests / Q000379:methods / Q000706:statistics & numerical data
D000596:Amino Acids; D000083722:Bacillus thuringiensis Toxins; D001426:Bacterial Proteins; D004731:Endotoxins; D006460:Hemolysin Proteins; D007306:Insecticides; C030956:insecticidal crystal protein, Bacillus Thuringiensis