摘要
改进更新匹配节点对的邻居节点得分之后的节点相似性得分计算方法,对匹配节点对的邻居节点相似性得分进行更新,综合使用节点间生物相似性得分、网络拓扑结构相似性得分和相互作用相似性得分对蛋白质相互作用网络进行匹配比对和迭代调整最佳匹配,以使得匹配结果更加贴近生物真实性.实验结果表明,给出的蛋白质相互作用网络全局比对算法整体上获得了更高的比对总分和检测到较多拥有共同基因本体的蛋白质对数.
The computational method of similarity score between nodes is improved when the scores of neighbors of matched node pairs have been updated, and the similarity scores of neighbors of matched node pairs are updated depending on the improved computa- tional method. By combining biological similarity score with network topology similarity score and interaction similarity score between nodes, the two protein interaction networks are aligned and the optimal matches are adjusted iteratively in order to obtain the matched results that are more close to the biological authenticity. Experimental results show that compared with existing algorithms, on the whole, the presented algorithm for global alignment of protein interaction networks obtains higher alignment scores and detects more protein pairs that have common gene ontology.
出处
《小型微型计算机系统》
CSCD
北大核心
2017年第4期808-812,共5页
Journal of Chinese Computer Systems
基金
国家自然科学基金项目(61462005)资助
广西自然科学基金项目(2014GXNSFAA118396)资助
关键词
蛋白质相互作用网络
全局比对
边正确率
比对总分
基因本体
protein-protein interaction networks
global alignment
edge correctness
sum score of alignment
gene ontology
