AI to help researchers see the bigger picture in cell biology
By providing holistic information on a cell, an AI-driven method could help scientists better understand disease mechanisms and plan experiments.
By providing holistic information on a cell, an AI-driven method could help scientists better understand disease mechanisms and plan experiments.
The MIT senior will pursue a master’s degree at Cambridge University in the U.K. this fall.
Read MoreAssistant Professor Yunha Hwang utilizes microbial genomes to examine the language of biology. Her appointment reflects MIT’s commitment to exploring the intersection of genetics research and AI.
Read MoreThe approach could apply to more complex tissues and organs, helping researchers to identify early signs of disease.
Read MoreProfessors Facundo Batista and Dina Katabi, along with three additional MIT alumni, are honored for their outstanding professional achievement and commitment to service.
Read MoreA new approach for testing multiple treatment combinations at once could help scientists develop drugs for cancer or genetic disorders.
Read MoreTrained with a joint understanding of protein and cell behavior, the model could help with diagnosing disease and developing new drugs.
Read MoreStuart Levine ’97, director of MIT’s BioMicro Center, keeps departmental researchers at the forefront of systems biology.
Read MoreFragFold, developed by MIT Biology researchers, is a computational method with potential for impact on biological research and therapeutic applications.
Read MoreWhitehead Institute and CSAIL researchers created a machine-learning model to predict and generate protein localization, with implications for understanding and remedying disease.
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