A team of researchers exploits high-content imaging to phenotype the effects of antimicrobial exposure on individual bacteria cells and screen for novel alternatives to existing antimicrobials. Projects include the development of polyclonal antibody serum, monoclonal antibodies, and functional assays that complement conventional molecular microbiology approaches. Here, in part 2, we explore the use of machine learning algorithms to predict how an organism is going to behave in response to an antimicrobial.