Data Clustering for the DNA Computing Readout Method Implemented on LightCycler and Based on Particle Swarm Optimization

In this work, particle swarm optimization (PSO) is applied to automate the DNA computing readout method based on a real-time polymerase chain reaction (PCR). Moreover, real-time amplification was performed and the TaqMan detection approach was used for the plan and the readout approach development. The most important part of the readout method is identifying two different reactions in the real-time PCR, which involve in vitro and in silico processes in order to inspect the placement of pairs of nodes in the Hamiltonian path problem. In addition, the real-time PCR experiment is implemented on the LightCycler System. Previously, manual method was exploited to classify two different output reactions of real-time PCR that was a time consuming process. In this study, by exploiting MATLAB the PSO has been implemented for clustering output reactions of real-time PCR and experimental results depict that the amplification response for YES and NO reactions can be clustered correctly.