Comparative analysis of machine learning algorithms on the microbial strain-specific AMP prediction
Boris Vishnepolsky, Maya Grigolava, Grigol Managadze, Andrei E. Gabrielian, Alex Rosenthal, Darrell E. Hurt, Michael Tartakovsky, Malak Pirtskhalava
The paper compares machine learning algorithms for predicting antimicrobial peptides (AMPs) specific to microbial strains, finding Random Forest and AdaBoost perform best with improved accuracy using genome characteristics.
Briefings in Bioinformatics · Jun 20, 2022Peer-reviewedBioinformatics