Lillian Eden

The KATMAP model, developed by researchers in the Department of Biology, can predict alternative cell splicing, which allows cells to create endless diversity from the same sets of genetic blueprints.

Although heart cells and skin cells contain identical instructions for creating proteins encoded in their DNA, they're able to fill such disparate niches because molecular machinery can cut out and stitch together different segments of those instructions to create endlessly unique combinations.

Alnylam Pharmaceuticals establishes named fund in honor of its co-founder, an MIT Institute Professor and Nobel laureate.

Assistant 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.

What if the Trojan horse had been pulled to pieces, revealing the ruse and fending off the invasion, just as it entered the gates of Troy? That's an apt description of a newly characterized bacterial defense system that chops up foreign DNA. Bacteria and the viruses that infect them, bacteriophages—phages for short—are ceaselessly at odds, with bacteria developing methods to protect themselves against phages that are constantly striving to overcome those safeguards.

From Boston to Moscow and across the U.S., Harriet Latham Robinson SM '61, PhD '65 has balanced an exciting career at the forefront of molecular biology with family, friends, and adventure.

In certain species of bacteria, the answer lies in shielding RNA transcripts from a quality-control factor called Rho.

In the study of bacteria, a longstanding dogma has held that two molecular machines—RNA polymerase, which leads the way in transcribing DNA into RNA, and ribosomes, which bring up the rear translating RNA into proteins—worked so closely in tandem that they were effectively attached. This close coupling of transcription and translation in bacteria was thought to be fundamental to gene expression, in part because the trailing ribosome could shield nascent gene products from an effective and omnipresent quality-control protein called Rho.

A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.

A protein's function is determined by its structure, and structure—the way a protein folds—is determined by its sequence of amino acids, the building blocks of proteins.