Table 1

Team Name	Members	Affiliation	Rank	Type of method	References
B Team	Kevin Y.Yip, Roger P. Alexander, Koon-Kiu Yan and Mark Gerstein	Yale University, USA	1st on all sizes	Statistical Method	[2]
USMtec347	Peng Li and Chaoyang Zhang	University of Mississippi, USA	2nd on size 10, 2nd on size 50	Bayesian network	-
Bonneau	Aviv Madar, Alex Greenfield, Eric Vanden-Eijnden, and Richard Bonneau	New York University, USA	2nd on size 100	Dynamical Model	[3-5]
Intigern	Xuebing Wu, Feng Zeng, and Rui Jiang	Tsinghua University, China	3rd on size 10, 3rd on size 100	Statistical Method	-
Zuma	Tarmo Aijo and Lahdesmaki	Tampere University of Technology, Finland	3rd on size 50	Dynamical Model	[6]

Table 1: Shows the top five best performing methods in inferring the network motifs in regulatory networks. In contrast, these represented errors in inferring the network motifs in regulatory networks may vary from networks to networks, so the efficiency of the methods should be cautiously studied based on the complexity of networks under study [20].