New model predicts a chemical reaction’s point of no return
Chemists could use this quick computational method to design more efficient reactions that yield useful compounds, from fuels to pharmaceuticals.
School of Science
MIT’s McGovern Institute is shaping brain science and improving human lives on a global scale
A quarter century after its founding, the McGovern Institute reflects on its discoveries in the areas of neuroscience, neurotechnology, artificial intelligence, brain-body connections, and therapeutics.
Making AI-generated code more accurate in any language
A new technique automatically guides an LLM toward outputs that adhere to the rules of whatever programming language or other format is being used.
At the core of problem-solving
Stuart Levine ’97, director of MIT’s BioMicro Center, keeps departmental researchers at the forefront of systems biology.
An ancient RNA-guided system could simplify delivery of gene editing therapies
The programmable proteins are compact, modular, and can be directed to modify DNA in human cells.
AI system predicts protein fragments that can bind to or inhibit a target
FragFold, developed by MIT Biology researchers, is a computational method with potential for impact on biological research and therapeutic applications.
AI model deciphers the code in proteins that tells them where to go
Whitehead Institute and CSAIL researchers created a machine-learning model to predict and generate protein localization, with implications for understanding and remedying disease.
Introducing the MIT Generative AI Impact Consortium
The consortium will bring researchers and industry together to focus on impact.
With generative AI, MIT chemists quickly calculate 3D genomic structures
A new approach, which takes minutes rather than days, predicts how a specific DNA sequence will arrange itself in the cell nucleus.
For healthy hearing, timing matters
Machine-learning models let neuroscientists study the impact of auditory processing on real-world hearing.