Andrei E. Gabrielian

This study shows that culturing Mycobacterium tuberculosis from sputum samples accurately mirrors the genetic diversity found in the original clinical samples, with high variant agreement and correlation.

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.