Using fuzzy logic inference algorithm to recover molecular genetic regulatory networks - Jing Yu; Wang, P.P. (NAFIPS - 2004 Annual Meeting of the North American Fuzzy Information Processing Society, 2004)
Network inference algorithms are powerful computational tools for identifying potential causal interactions among variables from observational data. Fuzzy logic has inherent capability of handling noisy data, so it becomes a tool we use to develop our inference algorithm. Here, we use a simulation approach to test and improve the algorithm. Our fuzzy logic inference algorithm works reasonably well in recovering the underlying regulatory network.