Faculty Opinions recommendation of A White-Box Machine Learning Approach for Revealing Antibiotic Mechanisms of Action.

Abstract

Current machine learning techniques enable robust association of biological signals with measured phenotypes, but these approaches are incapable of identifying causal relationships. Here we develop an integrated "white-box" biochemical screening, network modeling and machine learning approach for revealing causal mechanisms and apply this approach towards understanding antibiotic efficacy. We counter-screen diverse metabolites against bactericidal antibiotics in Escherichia coli and simulate their corresponding metabolic states using a genome-scale metabolic network model. Regression of the measured screening data on model simulations reveals that