Mutation Resistant Target Prediction Algorithm in PCR Based Diagnostic Applications
- Authors: Osman Doluca1, Murat Sayan2
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View Affiliations Hide Affiliations1 Department of Biomedical Engineering, Izmir University of Economics, Izmir, Turkey 2 Faculty of Medicine, Clinical Laboratory, Kocaeli University, PCR Unit, Kocaeli, Turkey
- Source: Applied Machine Learning and Multi-Criteria Decision-Making in Healthcare , pp 272-283
- Publication Date: November 2021
- Language: English
Mutation Resistant Target Prediction Algorithm in PCR Based Diagnostic Applications, Page 1 of 1
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Highly mutable organisms often challenge primer design for diagnostic PCR kit manufacturers due to new mutations occurring in hybridization sites. Novel variants may require reconsideration of the existing PCR primers and even result in misdiagnosis. While conserved sequences are often the main target of primer design algorithms, they often do not consider possible new mutants. We represent a generalizable algorithm for filtration of the sequence to identify conserved sequences and the less likely regions to mutate. Primers selected from the filtered sequences are expected to target regions with lower mutation rates and consecutively act indifferent to more variants of a target pathogen, providing long-lasting primers and less frequent primer redesign.
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