Analysis of SARS-CoV-2 RNA-Sequences by Interpretable Machine Learning Models
Marika Kaden, Katrin Sophie Bohnsack, Mirko Weber, Mateusz Kudła, Kaja Gutowska, Jacek Błażewicz, Thomas Villmann
The paper applies interpretable machine learning to classify and analyze SARS-CoV-2 sequences, identifying potential new virus types through rejected classifications.
bioRxiv · May 15, 2020 · PreprintBioinformatics