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Gene Regulatory Networks (GRNs) represent the causal relations among the genes and provide insight on the cellular functions and the mechanism of the diseases. GRNs can be inferred from gene expression data by a number of algorithms, e.g. Boolean networks, Bayesian networks, and differential equations. While reliable inference of GRNs is still an open problem, new algorithms need to be developed....
Fuzzy Cognitive Maps (FCMs) can represent causal relations among concepts in the form of directed weighted graphs. Learning FCMs from data is a difficult task because of the large number of candidate FCMs. The goal of learning FCMs is to find good weights for the FCM so that the response of the learned FCM should be as close to the observed data as possible. The number of variables to be optimized...
Ant colony system (ACS) and a few improved ant colony optimization (ACO) methods for solving optimization problems with continuous domain were studied. Based on these work, a new ACO method for solving nonlinear geophysical multi-parameter inversion was presented. Several techniques are employed, such as decimal coding, mapping mechanism, roulette wheel selection of genetic algorithm (GA), renormalization,...
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