A machine learning approach to define antimalarial drug action from heterogeneous cell-based screens

Jake Baum
Drug resistance threatens the effective prevention and treatment of an ever-increasing range of human infections. This highlights an urgent need for new and improved drugs with novel mechanisms of action to avoid cross-resistance. Current cell-based drug screens are, however, restricted to binary live/dead readouts with no provision for mechanism of action prediction. Machine learning methods are increasingly being used to improve information extraction from imaging data. Such methods, however, work poorly with heterogeneous cellular phenotypes...

Registration Year

  • 2021
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Resource Types

  • Image
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Affiliations

  • Google (United States)
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  • Imperial College London
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