基于模体中心结构的蛋白质复合物识别算法

基于蛋白质相互作用的网络有明显模块化特征, 其对预测蛋白质功能、解释特定的生物进程具有重要作用, 网络模体是复杂网络演化的 重要拓扑结构, 其代表了复杂系统中的重要功能单元, 具有进化保守性的特性, 提出一种新的基于网络模体为核心节点组的蛋白质复合物识别算法. 该算法根据蛋白质相互作用网络的拓扑特性, 将模体作为蛋白质复合物的中心结构体, 并基于中心结构体进行二层节点扩充, 能准确有效地识别蛋白质复合物. 并且将复合物二维网络进行三维转化, 从而更直观清晰地展示复合物的结构体特征. 实验结果验证了该算法的有效性及可行性.

Protein Complex Recognition Algorithm Based on Motif Center Structure

Network based on protein-protein interaction (PPI) had a obvious modular characteristics, which played an important role in predicting protein functions and explaining specific biological processes. Network motif was an important topology for the evolution of complex networks. It represented important functional units in complex systems and had the characteristics of evolutionary conservation. We proposed a new protein complex recognition algorithm based on network motif as the core node group.  According to the topological characteristics of the PPI network, the algorithm took  motifs as central structures of the protein complexes, and expanded the two-layer nodes based on central structure, which could accurately and effectively identify protein complexes. The 2D network of the protein complexes was transformed into 3D network, so as to show  the structural characteristics of the protein complexes more intuitively and clearly. The experimental results verify the effectiveness and feasibility of the algorithm.