Research on mining key genes of abiotic stress resistance in crops based on multi-objective genetic programming
In order to reduce the invalid genes in high-dimensional genes and mine the key genes for abiotic stress resistance of crops,a multi-objective genetic programming based method was proposed to mine the key genes for abiotic stress resistance of crops.A method for feature selection and classification of high-dimensional data based on multi-objective genetic programming(MONSGP)was proposed by combining genetic programming(GP)and multi-objective optimization algorithms NSGA-II.The method aimed to optimize recall,accuracy,and number of features to obtain the optimal Pareto solution set.The optimal classifier selection strategy was used to select the classifier with the best performance and a small number of features from the optimal solution set as the optimal classifier.Experiments on 9 NCBI high-dimensional gene datasets have showed that MONSGP can achieve better classification performance with fewer features compared to standard GP classification algorithms and three latest GP classification algorithms.GO functional enrichment analysis confirmed that the genes screened by MONSGP were related to abiotic stress and had biological significance.
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