Background: The information provided by dense genome-wide markers using high throughput technology is of considerable potential in human disease studies and livestock breeding pro...
Ross K. Shepherd, Theo H. E. Meuwissen, John A. Wo...
This work addresses the need for stateful dataflow programs that can rapidly sift through huge, evolving data sets. These data-intensive applications perform complex multi-step c...
Dionysios Logothetis, Christopher Olston, Benjamin...
Background: There has been considerable effort focused on developing efficient programs for tagging single-nucleotide polymorphisms (SNPs). Many of these programs do not account f...
Christopher K. Edlund, Won H. Lee, Dalin Li, David...
In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
We investigate the following question. Do populations of evolving agents adapt only to their recent environment or do general adaptive features appear over time? We find statistica...