基于蚁群聚类的动态加权PPI网络复合物挖掘

Mining protein complexes based on ant colony clustering in dynamic weighted PPI network

针对基于蚁群聚类的蛋白质复合物挖掘算法中,静态PPI网络难以真实反映细胞的动态特性,收敛速度较慢、聚类准确性和召回率不高等问题,提出一种基于模糊粒度和紧密度的蚁群聚类动态加权PPI网络复合物挖掘方法(FGCDACC-DPC)。首先基于动态PPI网络的拓扑特性和生物特性设计了综合性权值度量(comprehensive weight metric,CWM),准确描述了蛋白质之间的相互作用;其次根据复合物的基本特征,构建一组稠密且高度共表达的复合核,然后设计模糊粒度和紧密度的拾起放下模型对其余节点聚类,降低了计算复杂度和随机性,加快聚类速度;最后基于功能信息传递和时序功能相关的思想分别构建了局部和全局权值更新策略,实现不同代蚁群和不同时刻网络之间的功能信息传递,提高聚类准确性。将FGCDACC-DPC算法应用在DIP数据上进行复合物挖掘,实验结果表明该算法的精度和召回率较高,能够较准确地识别蛋白质复合物。

Since static PPI network are difficult to truly reflect the dynamic character of cells,the convergence speed is slow,cluster precision and recall is low in mining protein complex based on ant colony clustering,this paper proposed an ant colony clustering algorithm based on fuzzy granular and closeness degree to mine protein complexes in dynamic weighted PPI network,named FGCDACC-DPC(joint fuzzy granular and closeness degree ant colony clustering-DPC).First,based on the topological and biological characteristics of the PPI network,it designed a comprehensive weight metric(CWM)to accurately describe the interaction between proteins.Second,this method constructed a series of dense and highly co-expressed complex core based on the basic characteristic of the complexes,then it employed the picking and dropping operations,which based on fuzzy granular and closeness degree,to cluster the nodes in PPI network,in order to reduce effectively the computational complexity and randomness,speed up the clustering speed.Finally,this algorithm designed a local and global strategy founded on function transmission and timing functional relevance theory for weight’s update,which achieved the function transmission between different generations of ant colonies and networks at different times to effectively improve clustering accuracy.FGCDACC-DPC algorithm was used to mine protein complexes on DIP data.Experimental results demonstrate that this algorithm has better performance on precision and recall,which is more reasonable to identify protein complexes.