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.
By sidestepping the need for costly interventions, a new method could potentially reveal gene regulatory programs, paving the way for targeted treatments.
Professors Matthew Vander Heiden and Fan Wang, along with five MIT alumni, are honored for their outstanding professional achievement and commitment to service.
“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.
“He dived deep, even into cold water, but came out stronger and brought along others for a joyous adventure.”
Professor who uses a cross-disciplinary approach to understand human diseases on a molecular and cellular level succeeds Elazer Edelman.
The model could help clinicians assess breast cancer stage and ultimately help in reducing overtreatment.
PhD student Xinyi Zhang is developing computational tools for analyzing cells in the age of multimodal data.
A new gene-silencing tool shows promise as a future therapy against prion diseases and paves the way for new approaches to treating disease.
Twelve finalists participated in initiative and 2023-24 MIT-Royalty Pharma Prize Competition, designed to support female biotech pioneers.
Fifteen new faculty members join six of the school’s academic departments.
Guoping Feng, Piotr Indyk, Daniel Kleitman, Daniela Rus, Senthil Todadri, and nine alumni are recognized by their peers for their outstanding contributions to research.
By providing plausible label maps for one medical image, the Tyche machine-learning model could help clinicians and researchers capture crucial information.
The junior, who is majoring in computer science and molecular biology, wants to “make it a norm to lift others as I continue to climb.”
Moved by the human devastation and scientific conundrum of Alzheimer’s, William Li seeks to work on therapies for the disease.
With the new technique, MIT researchers hope to identify mutations that could be targeted with new cancer therapies.