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GECCO
2006
Springer
202views Optimization» more  GECCO 2006»
15 years 10 months ago
Inference of genetic networks using S-system: information criteria for model selection
In this paper we present an evolutionary approach for inferring the structure and dynamics in gene circuits from observed expression kinetics. For representing the regulatory inte...
Nasimul Noman, Hitoshi Iba
GECCO
2006
Springer
167views Optimization» more  GECCO 2006»
15 years 10 months ago
Estimating the destructiveness of crossover on binary tree representations
In some cases, evolutionary algorithms represent individuals as typical binary trees with n leaves and n-1 internal nodes. When designing a crossover operator for a particular rep...
Luke Sheneman, James A. Foster
GECCO
2006
Springer
172views Optimization» more  GECCO 2006»
15 years 10 months ago
Evolving boolean networks to find intervention points in dengue pathogenesis
We use probabilistic boolean networks to simulate the pathogenesis of Dengue Hemorraghic Fever (DHF). Based on Chaturvedi's work, the strength of cytokine influences are mode...
Philip Tan, Joc Cing Tay
GECCO
2006
Springer
161views Optimization» more  GECCO 2006»
15 years 10 months ago
The LEM3 implementation of learnable evolution model and its testing on complex function optimization problems
1 Learnable Evolution Model (LEM) is a form of non-Darwinian evolutionary computation that employs machine learning to guide evolutionary processes. Its main novelty are new type o...
Janusz Wojtusiak, Ryszard S. Michalski
GECCO
2006
Springer
156views Optimization» more  GECCO 2006»
15 years 10 months ago
Probabilistic modeling for continuous EDA with Boltzmann selection and Kullback-Leibeler divergence
This paper extends the Boltzmann Selection, a method in EDA with theoretical importance, from discrete domain to the continuous one. The difficulty of estimating the exact Boltzma...
Yunpeng Cai, Xiaomin Sun, Peifa Jia