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» Classification of Random Boolean Networks
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BMCBI
2007
110views more  BMCBI 2007»
13 years 5 months ago
Analysis of feedback loops and robustness in network evolution based on Boolean models
Background: Many biological networks such as protein-protein interaction networks, signaling networks, and metabolic networks have topological characteristics of a scale-free degr...
Yung-Keun Kwon, Kwang-Hyun Cho
GECCO
2008
Springer
179views Optimization» more  GECCO 2008»
13 years 6 months ago
Evolution of discrete gene regulatory models
Gene regulatory networks (GRNs) are complex control systems that govern the interaction of genes, which ultimately control cellular processes at the protein level. GRNs can be ted...
Afshin Esmaeili, Christian Jacob
GECCO
2009
Springer
150views Optimization» more  GECCO 2009»
13 years 12 months ago
Discrete dynamical genetic programming in XCS
A number of representation schemes have been presented for use within Learning Classifier Systems, ranging from binary encodings to neural networks. This paper presents results fr...
Richard Preen, Larry Bull
CC
2010
Springer
282views System Software» more  CC 2010»
13 years 3 months ago
Lower Bounds on the Randomized Communication Complexity of Read-Once Functions
Abstract. We prove lower bounds on the randomized two-party communication complexity of functions that arise from read-once boolean formulae. A read-once boolean formula is a formu...
Nikos Leonardos, Michael Saks
CEC
2003
IEEE
13 years 9 months ago
Dynamics of gene expression in an artificial genome
Abstract- Complex systems techniques provide a powerful tool to study the emergent properties of networks of interacting genes. In this study we extract models of genetic regulator...
Kai Willadsen, Janet Wiles