Background: Discovering the genetic basis of common genetic diseases in the human genome represents a public health issue. However, the dimensionality of the genetic data (up to 1...
Raphael Mourad, Christine Sinoquet, Philippe Leray
Background: During the most recent decade many Bayesian statistical models and software for answering questions related to the genetic structure underlying population samples have...
Genetic Algorithms are very powerful search methods that are used in different optimization problems. Parallel versions of genetic algorithms are easily implemented and usually in...
A novel machine language genetic programming system that uses one-dimensional core memories is proposed and simulated. The core is compared to a biochemical reaction space, and in ...
A Bayesian network model is a popular technique for data mining due to its intuitive interpretation. This paper presents a semantic genetic algorithm (SGA) to learn a complete qual...