Space pruning monotonic search for the non-unique probe selection problem

Authors:
Elisa Pappalardo;Beyza Ahlatcioglu Ozkok;Panos M. Pardalos
Affiliations:
Department of Mathematics and Computer Science, University of Catania, Catania, Italy;Department of Mathematics, Yildiz Technical University, Istanbul, Turkey;Department of Industrial and Systems Engineering, Center for Applied Optimization, University of Florida, Florida, USA
Venue:
International Journal of Bioinformatics Research and Applications
Year:
2014

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Abstract

Identification of targets, generally viruses or bacteria, in a biological sample is a relevant problem in medicine. Biologists can use hybridisation experiments to determine whether a specific DNA fragment, that represents the virus, is presented in a DNA solution. A probe is a segment of DNA or RNA, labelled with a radioactive isotope, dye or enzyme, used to find a specific target sequence on a DNA molecule by hybridisation. Selecting unique probes through hybridisation experiments is a difficult task, especially when targets have a high degree of similarity, for instance in a case of closely related viruses. After preliminary experiments, performed by a canonical Monte Carlo method with Heuristic Reduction MCHR, a new combinatorial optimisation approach, the Space Pruning Monotonic Search SPMS method, is introduced. The experiments show that SPMS provides high quality solutions and outperforms the current state-of-the-art algorithms.