Computer-assisted Biology: Decoding Noisy Data to Predict Cell Growth

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Researchers from The University of Tokyo Institute of Industrial Science used artificial intelligence to obtain a more objective understanding of cell growth and division without preconceived assumptions. Using a deep-learning neural network, they were able to more accurately model the complex processes that affect cell size over time. This work may lead to advances in microbiology and industrial production of microorganisms.

2021.07.09

Press Release

Computer-assisted Biology: Decoding Noisy Data to Predict Cell Growth

Researchers at The University of Tokyo Institute of Industrial Science use artificial intelligence to predict the size of cells over time without the need for simplifying assumptions, which may lead to a new understanding of microbiology principles and improved drug manufacturing from recombinant bacteria

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