Caroline Uhler blends machine learning, statistics, and biology to understand how our bodies respond to illness
Image: Adam Glanzman
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News & Events
News
Seeking the cellular mechanisms of disease, with help from machine learning
Posted
April 6, 2021
News
Method offers inexpensive imaging at the scale of virus particles
Posted
March 29, 2021
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...
News
Imaging method reveals a "symphony of cellular activities"
Posted
November 23, 2020
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...
News
Machine learning uncovers potential new TB drugs
Posted
October 15, 2020
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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