Interpretable machine learning reveals a diverse arsenal of anti-defenses in bacterial viruses
A. Lopatina, M. Ferenc, N. Bartlau, M. Wolfram, K. Steensen, S. Muscia, F. Hussain, M. Schnurer, L. Afjehi-Sadat, S. Pollak, M. F. Polz
The paper uses interpretable machine learning to identify anti-defense genes in bacterial viruses, revealing their ability to counteract diverse bacterial immune systems.
bioRxiv · Jun 14, 2024 · PreprintMicrobiology