Using machine learning models to predict the impact of template mismatches on polymerase chain reaction assay performance

Using machine learning models to predict the impact of template mismatches on polymerase chain reaction assay performance

Abstract Molecular assays are critical tools for the diagnosis of infectious diseases. These assays have been extremely valuable during the COVID pandemic, used to guide both patient management and infection control strategies. Sustained transmission and unhindered proliferation of the virus during...

Full description

Saved in:
Bibliographic Details
Main Authors: Brittany Knight, Taylor Otwell, Michael P. Coryell, Jennifer Stone, Phillip Davis, Bryan Necciai, Paul E. Carlson, Shanmuga Sozhamannan, Alyxandria M. Schubert, Yi H. Yan
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:Scientific Reports
Subjects:
Signature erosion
qPCR performance
In silico prediction
False negative result
Supervised learning
Online Access:https://doi.org/10.1038/s41598-025-98444-8
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1038/s41598-025-98444-8

Similar Items