DNA
DNA

3 Questions: Building predictive models to characterize tumor progression

Assistant Professor Matthew Jones is working to decode molecular processes on the genetic, epigenetic, and microenvironment levels to anticipate how and when tumors evolve to resist treatment.

3 Questions: On biology and medicine’s “data revolution”

Professor Caroline Uhler discusses her work at the Schmidt Center, thorny problems in math, and the ongoing quest to understand some of the most complex interactions in biology.

Rationale engineering generates a compact new tool for gene therapy

Researchers redesign a compact RNA-guided enzyme from bacteria, making it an efficient editor of human DNA.

With AI, researchers predict the location of virtually any protein within a human cell

Trained with a joint understanding of protein and cell behavior, the model could help with diagnosing disease and developing new drugs.

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.

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.

Fifteen Lincoln Laboratory technologies receive 2024 R&D 100 Awards

The innovations map the ocean floor and the brain, prevent heat stroke and cognitive injury, expand AI processing and quantum system capabilities, and introduce new fabrication approaches.

A new computational technique could make it easier to engineer useful proteins

MIT researchers plan to search for proteins that could be used to measure electrical activity in the brain.