Discovering frequent probability pattern in uncertain biological networks by circuit simulation method

In the field of bioinformatics, many types of data can be represented as the topological graph, such as protein-protein interaction network. Milo proposed the concept of biological motif 0 on Science, which is referred as a substructure that appears in different parts of a network, and appears significantly more frequently than in a random network. Research shows that the motif recognition is important for many biological studies. As the life process itself is a dynamic process, the motif of the same function may be made up of the subgraphs which may slightly differ in topology, so Berg etc. [2] proposed probability motif mining algorithms in the biological network. And science graph data are obtained with the inevitable experimental error or noise data, and some biological network data carries probability information. Since biological evolution itself is a mutant selection process, the input of biological networks should also be a probabilistic network. Therefore, it is more intuitively and practically significantly to mine probability motif in the probability biological network.