Evaluation of subgraph searching algorithms detecting network motif in biological networks

摘要

Despite several algorithms for searching subgraphs in motif detection presented in the literature, no effort has been done for characterizing their performance till now. This paper presents a methodology to evaluate the performance of three algorithms: edge sampling algorithm (ESA), enumerate subgraphs (ESU) and randomly enumerate subgraphs (RAND-ESU). A series of experiments are performed to test sampling speed and sampling quality. The results show that RAND-ESU is more efficient and has less computational cost than other algorithms for large-size motif detection, and ESU has its own advantage in small-size motif detection.