Microsatellite detection and consensus sequence verification by virtual PCR and machine learning
Kolychev, Dmitri Sergeevich
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Microsatellites, or simple sequence repeats, are genetic loci where several nucleotide bases are repeated in tandem. Since they can be easily found by Polymerase Chain Reaction (PCR) using unique flanking primers, they are considered excellent genetic markers in making genetic linkage maps among other things. In this thesis we present Microsatellite Polymorphism Finder (MSPF), a program that detects and then verifies microsatellites by modeling PCR digitally from an Expressed Sequence Tag (EST) or a shotgun-sequencing database without the overhead required to perform PCR chemically with human intervention. Moreover, a machine learning enhanced version of MSPF improves the accuracy of microsatellite verification.