Caroline Uhler blends machine learning, statistics, and biology to understand how our bodies respond to illness
Image: Adam Glanzman
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Caroline Uhler blends machine learning, statistics, and biology to understand how our bodies respond to illness
Image: Adam Glanzman
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Image: Ella Maru Studio, Credit: Ruixuan Guo and Boyden Lab
Using an ordinary light microscope, MIT engineers have devised a technique for imaging biological samples with...
Fluorescent imaging technique simultaneously captures different signal types from multiple locations in a live cell.
Within a single cell, thousands of molecules, such as proteins, ions, and other signaling molecules, work together to perform all kinds of functions...
Computational method for screening drug compounds can help predict which ones will work best against tuberculosis or other diseases.
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.
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