Non-unique oligonucleotide microarray probe selection method based on genetic algorithms

In order to accurately measure the gene expression levels in microarray experiments, it is crucial to design unique, highly specific and sensitive oligonucleotide probes for the identification of biological agents such as genes in a sample. Unique probes are hard to obtain for closely related genes such as the known strains of HIV genes. The non-unique probe selection problem is to select a probe set that is able to uniquely identify targets, in a biological sample, while containing a minimal number of probe. This is a NP-hard problem and this paper contributes the first evolutionary method for finding near minimal non-unique probe sets. When used on benchmark data sets, our approach consistently performed better than three recently published methods. We also obtained results that are at least comparable to those of the current state-of-the-art heuristic.