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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 webinar will discuss data from a recent real-world comparison study evaluating performance of two cell-free DNA methodologies as first-line prenatal screens.

Mar
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Isoplexis

This webinar will discuss the application of single-cell proteomics and immune-imaging in adoptive cell therapy (ACT) for cancer.