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A new approach to modeling complex biological systems
MIT biological engineers developed a computational approach to extracting useful information from large biological datasets. They showed they could unravel interactions that determine how the immune system responds to tuberculosis vaccination and infection.
“We’ve landed on a computational modeling framework that allows prediction of effects of perturbations in a highly complex system, including multiple scales and many different types of components,” says Lauffenburger, the senior author of the new study. Using computational approaches such as machine learning, scientists can use this data to train models to predict a specific output based on a given set of inputs — for example, whether a vaccine will generate a robust immune response. In hopes of developing more effective TB protection, researchers have been testing whether delivering the BCG vaccine intravenously or by inhalation might provoke a better immune response than injecting it.
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