A causal theory for studying the cause-and-effect relationships of genes
By sidestepping the need for costly interventions, a new method could potentially reveal gene regulatory programs, paving the way for targeted treatments.
Broad Institute
A fast and flexible approach to help doctors annotate medical scans
“ScribblePrompt” is an interactive AI framework that can efficiently highlight anatomical structures across different medical scans, assisting medical workers to delineate regions of interest and abnormalities.
AI model identifies certain breast tumor stages likely to progress to invasive cancer
The model could help clinicians assess breast cancer stage and ultimately help in reducing overtreatment.
School of Engineering welcomes new faculty
Fifteen new faculty members join six of the school’s academic departments.
New AI method captures uncertainty in medical images
By providing plausible label maps for one medical image, the Tyche machine-learning model could help clinicians and researchers capture crucial information.
Using AI, MIT researchers identify a new class of antibiotic candidates
These compounds can kill methicillin-resistant Staphylococcus aureus (MRSA), a bacterium that causes deadly infections.
Search algorithm reveals nearly 200 new kinds of CRISPR systems
By analyzing bacterial data, researchers have discovered thousands of rare new CRISPR systems that have a range of functions and could enable gene editing, diagnostics, and more.
A more effective experimental design for engineering a cell into a new state
By focusing on causal relationships in genome regulation, a new AI method could help scientists identify new immunotherapy techniques or regenerative therapies.
MIT scientists build a system that can generate AI models for biology research
Is it possible to build machine-learning models without machine-learning expertise? Jim Collins, the Termeer Professor of Medical Engineering and Science in the Department of Biological Engineering at MIT and the…
New model offers a way to speed up drug discovery
By applying a language model to protein-drug interactions, researchers can quickly screen large libraries of potential drug compounds.