This paper describes an evolutionary clustering algorithm, which can partition a given dataset automatically into the optimal number of groups through one shot of optimization. The...
—In metabolic engineering it is difficult to identify which set of genetic manipulations will result in a microbial strain that achieves a desired production goal, due to the co...
Background: Data mining in large DNA sequences is a major challenge in microbial genomics and bioinformatics. Oligonucleotide usage (OU) patterns provide a wealth of information f...
Hamilton Ganesan, Anna S. Rakitianskaia, Colin F. ...
Abstract. In this work, a Simulated Annealing (SA) algorithm is proposed for a Metabolic Engineering task: the optimization of the set of gene deletions to apply to a microbial str...
In this paper, we present a novel evolutionary algorithm, called NOCEA, which is suitable for Data Mining (DM) clustering applications. NOCEA evolves individuals that consist of a ...
Ioannis A. Sarafis, Philip W. Trinder, Ali M. S. Z...