Machine Learning Approach to Antibiotic Discovery

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Summary

Graphical abstract from Stokes et al., 2020. Diagrams the computational workflow of the machine learning approach to antibiotic discovery.

By Reed Crocker
Biology 238: Microbiology
Spring 2020

Antibiotics are essential for the modern practice of medicine. However, the rise of antibiotic-resistant bacteria present new challenges to paradigm in medical treatment. Discovery and development of novel antibiotics is not meeting the pace of microbial resistance. The arms race against pathogenic bacteria has prompted significant research into new modes of antibiotic discovery. One rapidly expanding sector of this research uses a high throughput, machine learning approach to predict candidate antibiotics in silico.

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Traditional Discovery Methods

Research about how the gradient control enables higher tolerance.

Advantages of Machine Learning in Antibiotic Discovery

High throughput, less costly, quicker.

Future

Where this research might continue to.

References

Authored for BIOL 238 Microbiology, taught by Joan Slonczewski, 2018, Kenyon College.