Algorithm For Biologicakl Network Alignment Based On Metabolic Pathways

An important tool for analyzing biological networks is the ability to perform homology searches, which is completed through the alignment of networks. In recent years, network comparison techniques promise to take an increasing role in the field of biological research, this problem has been widely and deeply studied and many efficient algorithms are available.In this paper, we firstly introduced some efficient algorithms, and analyzed that all this algorithms proposed to solve this problem by restricting the topology of the graphs. This restriction, however, severely limits the applicability of their algorithm. Based on the analysis of the existing algorithm, we present a new algorithm. We firstly abstract the metabolic pathways as the graph and we modeled the alignment based on pathway. Then we make a scoring mechanism by classifying the enzymes using their EC numbers.We do experiments using metabolic pathways from the KEGG database. The simulation results show that our algorithm has a wider range of applicability than the restricted approach. So, our algorithm is effective and applicable.