基于蛋白质相互作用网络图的聚类方法

Clastering method based on protein-protein interaction network graph

依据人类AD(Alzheimer's Disease)相关蛋白质相互作用网络图,利用基于算术平均最小值——AAMV(Arithmetic Average Minimum Value)的K-means聚类方法对蛋白质进行聚类并预测4个孤立蛋白质的功能。分析结果表明:所得结果与用Maryland Bridge法及Korbel法所得结果非常相似。

The purpose of this study is to evaluate a novel clustering technique for clustering and detecting the isolated points in protein-protein interaction network,which iteratively refines clusters based on a combination of the K-means clustering algorithm and the Arithmetic Average Minimum Value （AAMV）.The result is that the algorithm is found to be effective at detecting clusters and identifying the isolated points in the protein-protefn interaction network graph with regard to human Alzheimer＇s Disease.The algorithm outperforms competing approaches and is capable of effectively predicting the function-unknown protein function.