Abstract
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.
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