Microbiology Meets Machine Learning

Artificially intelligent software has human-like ability to analyze host-pathogen interactions in microscopy images.

ruth williams
| 2 min read
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Computational systems called neural networks—based on the learning processes of biological brains—enable a form of machine learning that has the potential to help researchers interpret biological and medical images. Scientists who study how pathogens interact with host cells are now beginning to harness such technology.

“Most people in the [pathogen-host interactions] field were just manually counting—literally sitting there and assessing how many [parasites] per cell, how many in one of these vacuoles,” and so on, says parasitologist Eva Frickel of the Francis Crick Institute in London. “My students were losing hours and hours, days and weeks counting these events.”

Neural networks are used for all manner of image-processing tasks, such as face recognition, diagnostics, and self-driving cars, so Frickel thought such a system might offer a solution to her team’s problem. She teamed up with computational biologist Artur Yakimovich of the Medical Research Council’s Laboratory ...

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Meet the Author

  • ruth williams

    Ruth Williams

    Ruth is a freelance journalist.

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May 2019 The Scientist Issue
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