计算机与数字工程2024，Vol.52Issue(12)：3512-3516,3522,6.DOI:10.3969/j.issn.1672-9722.2024.12.007
基于改进遗传聚类的生物基因多序列分类方法
A Methodology for Modeling Multiple Sequence Classification of Biological Genes Based on Improved Genetic Clustering
摘要
Abstract
A multi-sequence classification model of biological genes based on improved genetic clustering is investigated to provide basic data for genetic engineering.A hidden Markov model(HMM)is used to model each gene sequence.The mechanism of selection,crossover and variation of the genetic algorithm is improved by using the quantum optimization algorithm.The improved genetic algorithm is used to search the cluster center.By dynamically adjusting the quantum rotation angle,the adaptive mutation operator is introduced to enhance the global search ability of the optimal cluster center.After the improved genetic algorithm is used to optimize the cluster center of the K-means clustering algorithm.The accurate classification of multiple gene sequences is achieved.The experimental results show that the method can achieve biological gene multi sequence classification,the samples with-in the class are densely distributed,and the samples between classes have a high degree of discrimination,with the average F1 score index reaching 93.45%.关键词
基因序列/隐马尔可夫模型/状态转移矩阵/K-means聚类算法/群中心/量子遗传算法Key words
gene sequence/hidden Markov model/state transition matrix/K-means clustering/cluster center/quantum ge-netic algorithm分类
信息技术与安全科学引用本文复制引用
钟娉婷,徐胜超..基于改进遗传聚类的生物基因多序列分类方法[J].计算机与数字工程,2024,52(12):3512-3516,3522,6.基金项目
国家自然科学基金面上项目(编号:61972444)资助. （编号:61972444）
