2018
DOI: 10.1371/journal.pone.0200962
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Optimization of multiplex quantitative polymerase chain reaction based on response surface methodology and an artificial neural network-genetic algorithm approach

Abstract: Multiplex quantitative polymerase chain reaction (qPCR) has found an increasing range of applications. The construction of a reliable and dynamic mathematical model for multiplex qPCR that analyzes the effects of interactions between variables is therefore especially important. This work aimed to analyze the effects of interactions between variables through response surface method (RSM) for uni- and multiplex qPCR, and further optimize the parameters by constructing two mathematical models via RSM and back-pro… Show more

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Cited by 9 publications
(5 citation statements)
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“…Hence, we developed a TaqMan-based fast multiplex quantitative real-time PCR assay for the simultaneous detection of dog cox1, human cytb and Leishmania kDNA in female sand flies. The addition of multiple primers and probes in a single reaction as well as changes in the number of cycles and annealing temperature can affect the specificity, sensitivity and efficiency of real-time PCR assays [23,24]. This is in fact one of the main obstacles to overcome while developing a multiplex real-time PCR assay [17].…”
Section: Discussionmentioning
confidence: 99%
“…Hence, we developed a TaqMan-based fast multiplex quantitative real-time PCR assay for the simultaneous detection of dog cox1, human cytb and Leishmania kDNA in female sand flies. The addition of multiple primers and probes in a single reaction as well as changes in the number of cycles and annealing temperature can affect the specificity, sensitivity and efficiency of real-time PCR assays [23,24]. This is in fact one of the main obstacles to overcome while developing a multiplex real-time PCR assay [17].…”
Section: Discussionmentioning
confidence: 99%
“…RSM, an effective statistical method and mathematical techniques in optimizing complex systems, is usually used to obtain the optimal parameters by constructing mathematical models and analysis of regression and variance [15,16,17]. By using RSM, the number of experimental trials was reduced and the interactions between independent variables were illustrated [18,19].…”
Section: Resultsmentioning
confidence: 99%
“…2013; Pan et al . 2018). We used single primer pairs to reduce the complexity and optimised the ratio of primers and probes for each species.…”
Section: Discussionmentioning
confidence: 99%