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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Jun
19
Sponsored by
ACD

This webinar will provide evidence for the use of RNA in situ hybridization (RNA ISH) as a replacement for immunohistochemistry (IHC) in cancer research and diagnostic applications.

Jun
21
Sponsored by
Roche

This webinar will provide a detailed look at how a genomics lab implemented next-generation sequencing (NGS) liquid biopsy assays into its in-house clinical research program.