计算机应用与软件2026，Vol.43Issue(1)：185-192,8.DOI:10.3969/j.issn.1000-386x.2026.01.025
基于双通道混合图神经网络的DNA结合蛋白识别
DNA-BINDING PROTEIN RECOGNITION BASED ON DUAL-CHANNEL HYBRID GRAPH NEURAL NETWORK
摘要
Abstract
The study of DNA-binding proteins has important significance and role in the field of biopharmaceuticals and clinical testing.Deep learning methods have significantly improved prediction accuracy,but have encountered bottlenecks in exploiting protein structure and evolutionary information.Therefore,this paper proposes a DNA-binding protein recognition method based on dual-channel hybrid graph neural network,which uses sequence alignment to find sequence evolution information,fuses graph attention network and graph isomorphic neural network,mines the key information of DNA-binding proteins contained in protein contact map and sequence evolution,and obtains high-precision protein representation.Experimental results show that the average accuracy of this method is improved by 9.49%compared with the average accuracy of the six typical methods on the independent test set.关键词
DNA结合蛋白/图注意力网络/蛋白质接触图/图同构神经网络/序列预处理Key words
DNA-binding protein/Graph attention networks/Protein contact map/Graph isomorphic net/Prepro-cessing of qequence分类
信息技术与安全科学引用本文复制引用
祁枢杰,陆卫忠,傅启明,马洁明,崔志明,吴宏杰..基于双通道混合图神经网络的DNA结合蛋白识别[J].计算机应用与软件,2026,43(1):185-192,8.基金项目
国家自然科学基金项目(62073231,61902272,61902271). （62073231,61902272,61902271）
