COVIDOUTCOME-estimating COVID severity based on mutation signatures in the SARS-CoV-2 genome

Database (Oxford) 2022-05-27

Summary:

Numerous studies demonstrate frequent mutations in the genome of SARS-CoV-2. Our goal was to statistically link mutations to severe disease outcome. We used an automated machine learning approach where 1594 viral genomes with available clinical follow-up data were used as the training set (797 'severe' and 797 'mild'). The best algorithm, based on random forest classification combined with the LASSO feature selection algorithm, was employed to the training set to link mutation signatures and...

Link:

https://pubmed.ncbi.nlm.nih.gov/33963845/?utm_source=Other&utm_medium=rss&utm_campaign=journals&utm_content=101517697&fc=None&ff=20220527014736&v=2.17.6

From feeds:

📚BioDBS Bibliography » Database (Oxford)

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Authors:

Ádám Nagy, Balázs Ligeti, János Szebeni, Sándor Pongor, Balázs Gyrffy

Date tagged:

05/27/2022, 01:47

Date published:

05/08/2021, 06:00