Arc News

Created by the labs of Brian Hie, Arc Innovation Investigator and Stanford Assistant Professor of Chemical Engineering, and Patrick Hsu, Arc Core Investigator and UC Berkeley Assistant Professor of Bioengineering, Evo was first introduced in a preprint earlier this year and has now been published in Science. Since the preprint was posted, the researchers have used Evo to design a functional CRISPR system unknown in nature, showing how this deeper understanding of biological sequences can yield new molecular tools.

Dave Burke is joining us today as Chief Technology Officer. He will lead our engineering efforts across computational technology development and machine learning to progress our understanding of biology.

Arc Institute, the research organization pioneering a new model for pursuing scientific breakthroughs, announced today the addition of seven leading scientists to its Investigator Program and Ignite Award cohorts.

Arc's Goodarzi Lab, in collaboration with the Gilbert Lab, discovered that mRNA can actively control its own expression using newly discovered "RNA switches." Arc postdoc Matvei Khoroshkin shares a look behind the paper published in Nature Methods.

The latest research from Dr. Lingyin Li’s lab, published in Molecular Cell, reveals a previously unknown mechanism that keeps our immune system in check. At the heart of this discovery is PELI2, a protein that prevents the STING pathway from overreacting to small amounts of cellular stress.

Arc’s Hsu Lab uncovers the first natural RNA-guided recombinase that can programmably insert, excise, or invert any two DNA sequences of interest.

Introducing Evo, a biological foundation model that generalizes across the fundamental languages of biology: DNA, RNA, and proteins. Evo is capable of both prediction tasks, and generative design from molecular to whole genome scale.

“There’s a huge unmet need in reducing the mortality rate of breast cancer,” said Li. “By identifying ENPP1’s role in suppressing the body’s immune response, our research is a significant step toward providing another effective treatment for patients living with breast cancer.”

At Arc, we're investing heavily in the infrastructure and expertise required to push forward the frontier of machine learning in biology across our faculty and Technology Centers. Part of our vision to advance the use of machine learning in biomedical research is to develop and disseminate computational resources and tools that enable reproducibility and support discovery throughout the scientific community.

We’re excited to provide this update on our growing scientific community, as the latest step in our 5-year trajectory towards 15 Core Investigators, five Science Fellows, five Technology Centers, and 20 Innovation Investigators.