Title:
Machine learning uncovers potential new TB drugs
Author:
Anne Trafton, Massachusetts Institute of Technology (MIT)
Published:
Tech Xplore, 15 October 2020
From the article:
Machine learning is a computational tool used by many biologists to analyze huge amounts of data, helping them to identify potential new drugs. MIT researchers have now incorporated a new feature into these types of machine-learning algorithms, improving their prediction-making ability.
Using this new approach, which allows computer models to account for uncertainty in the data they're analyzing, the MIT team identified several promising compounds that target a protein required by the bacteria that cause tuberculosis.
See also the scholarly article related to this TechXplore article:
Leveraging Uncertainty in Machine Learning Accelerates Biological Discovery and Design
by Brian Hie, Bryan D. Bryson & Bonnie A. Berger
Cell Systems, 15 October 2020