Using genetic algorithm and maximum clique to design multiplex PCR primers for sequential deletion applications
by Ren-Hao Pan; Rung-Ching Chen; Elong Lin; Yung-Kuan Chan; Yung-Fu Chen
International Journal of Data Mining and Bioinformatics (IJDMB), Vol. 14, No. 2, 2016

Abstract: Sequential deletion method is generally used to locate the functional domain of a protein. In contrast to the general Multiplex Polymerase Chain Reaction (MPCR) that requires multiple pairs of forward and reverse primers to extract the desired products, the MPCR for sequential deletion also needs multiple forward primers, which are clustered into several groups, but only a single compatible reverse primer in each corresponding group. In this study, a Genetic-Maximum-Clique (GMC) algorithm which combines the genetic algorithm for solving maximum clique problem is proposed to design the primers of MPCR. This algorithm obtains near-optimal primers that can be clustered in as few multiplex primer groups as possible for one PCR experiment. The results show that the algorithm can provide fewer groups for longer sequences. It is useful in assisting the researchers to design the primers for multiplex PCR experiments specific to sequential deletion applications. Furthermore, primers designed by the proposed GMC method has also been confirmed to be capable of covering the primers designed manually in previous investigations.

Online publication date: Sat, 13-Feb-2016

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