Kai-Chun Fan

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Multi-variate estimation of distribution algorithms (EDAs) build models via detecting interactions between genes and estimate the distributions to solve problems. EDAs have been applied for real world applications, but whether the models given by EDAs match what are really needed to solve the problems is yet unknown. This paper proposes using the number of(More)
Important advances have been made within in past few years in the treatment of glioma, however, the longterm prognosis after resection of glioma remains unsatisfactory as a result of a high incidence of recurrence. To solve this problem, many biologic therapies have been investigated. In the present study, we report a nanoparticle with properties for dual(More)
Cocaine dependence involves in the brain's reward circuit as well as nucleus accumbens (NAc), a key region of the mesolimbic dopamine pathway. Many studies have documented altered expression of genes and identified transcription factor networks and epigenetic processes that are fundamental to cocaine addiction. However, all these investigations have focused(More)
Existing EDAs learn linkages starting from pairwise interactions. The characteristic function which indicates the relations among variables are binary. In other words, the characteristic function indicates that there exist or not interactions among variables. Empirically, it can occur that two variables should be sometimes related but sometimes not. This(More)
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