New Melt Curve Machine Learning Method Enables Large Scale Genotyping of Sequence Variants | GenomeWeb

NEW YORK (GenomeWeb) — High-resolution melt curve analysis is a robust and simple way of querying the genotypes present in heterogeneous samples, since curve shapes and melting temperatures are related to nucleic acid sequence.

Now, researchers at Johns Hopkins and Stanford Universities have developed a method to pluck quantitative information about all sequence variants in a mixture. The method uses an algorithm relying on the iterative process of machine learning to automatically classify HRM curves, and can enable large-scale genotype assessment in unknown samples.

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This online seminar will highlight recent advances in the use of next-generation sequencing to detect drug-resistant mutations in patients with HIV or HCV. 

Mar
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This webinar will discuss how next-generation sequencing and digital PCR can be used in a complementary manner for liquid biopsies in order to improve patient care.