Truly autonomic networks ultimately require self-modifying, evolving protocol software. Otherwise humans must intervene in every situation that has not been anticipated at design t...
Lymphoma cancer classification with DNA microarray data is one of important problems in bioinformatics. Many machine learning techniques have been applied to the problem and produc...
Abstract. Bloat is a common and well studied problem in genetic programming. Size and depth limits are often used to combat bloat, but to date there has been little detailed explor...
Nicholas Freitag McPhee, Alex Jarvis, Ellery Fusse...
Extending the notion of inheritable genotype in genetic programming (GP) from the common model of DNA into chromatin (DNA and histones), we propose an approach of embedding in GP a...
Genetic programming (GP) based data fusion and AdaBoost can both improve in vitro prediction of Cytochrome P450 activity by combining artificial neural networks (ANN). Pharmaceuti...
William B. Langdon, S. J. Barrett, Bernard F. Buxt...