• krellor@kbin.social
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    11 months ago

    It doesn’t sound like it but they don’t have enough detail in the article to say.

    It sounds likey they are using a classification model that takes a vectorized text representation of molecules and classifies or scores them by their expected properties/reactivity. They took 39,000 molecules with known reactivity to MRSA to train the model, I assume to classify the structures. Once trained they can feed in arbitrary molecules into the trained model and see which ones are predicted to have antibiotic properties, which they can verify with bench work.

    They likely fed in molecules from classes of likely candidate structures, and the model helped focus and direct the wet work.

    I’m not up on the latest, but years ago I helped a similar project using FPGAs running statistical models to direct lab work.

    • Jerkface@lemmy.world
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      11 months ago

      I’d be interested to know why FPGAs were selected for this application. I’m not especially familiar with their use cases.

      • krellor@kbin.social
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        11 months ago

        This was years ago before GPU processing really took off, and we wanted the performance, but also, wanted to see if we could develop an affordable discrete lab device that could be placed in labs to aid in computationally directed bench work. So effectively, testing the efficacy of the models and designing ASICs to perform lab tests.