Scientists have developed artificial intelligence software that can create proteins that may be useful as vaccines, cancer treatments, or even tools for pulling carbon pollution out of the air. This research, reported today in the journal Science, was led by the University of Washington School of Medicine and Harvard University. The article is titled "Scaffolding protein functional sites using deep learning." "The proteins we find in nature are amazing molecules, but designed proteins can do so much more," said senior author David Baker, an HHMI Investigator and professor of biochemistry at UW Medicine. "In this work, we show that machine learning can be used to design proteins with a wide variety of functions." For decades, scientists have used computers to try to engineer proteins.

Scientists have developed artificial intelligence software that can create proteins that may be useful as vaccines, cancer treatments, or even tools for pulling carbon pollution out of the air. This research, reported today in the journal Science, was led by the University of Washington School of Medicine and Harvard University. The article is titled "Scaffolding protein functional sites using deep learning." "The proteins we find in nature are amazing molecules, but designed proteins can do so much more," said senior author David Baker, an HHMI Investigator and professor of biochemistry at UW Medicine. "In this work, we show that machine learning can be used to design proteins with a wide variety of functions."

In the everyday world, we can perform measurements with nearly unlimited precision. But in the quantum world—the realm of atoms, electrons, photons, and other tiny particles—this becomes much harder. Every measurement made disturbs the object and results in measurement errors. In fact, everything from the instruments used to the system's properties might impact the outcome, which scientists call noise. Using noisy measurements to control quantum systems, particularly in real-time, is problematic. So, finding the means for accurate measurement-based control is essential for use in quantum technologies like powerful quantum computers and devices for healthcare imaging.

Any convictions will be evaluated to determine if they directly relate to the responsibilities and requirements of the position. Having a conviction history will not automatically disqualify an applicant from being considered for employment.

Blend two or three metals together and you get an alloy that usually looks and acts like a metal, with its atoms arranged in rigid geometric patterns. But once in a while, under just the right conditions, you get something entirely new: a futuristic alloy called metallic glass that's amorphous, with its atoms arranged every which way, much like the atoms of the glass in a window. Its glassy nature makes it stronger and lighter than today's best steel, plus it stands up better to corrosion and wear. Even though metallic glass shows a lot of promise as a protective coating and alternative to steel, only a few thousand of the millions of possible combinations of ingredients have been evaluated over the past 50 years, and only a handful developed to the point that they may become useful. Now a group led by scientists at the Department of Energy's SLAC National Accelerator Laboratory, the National Institute of Standards and Technology (NIST) and Northwestern University has reported a shortcut for discovering and improving metallic glass -- and, by extension, other elusive materials -- at a fraction of the time and cost.

Injuries to the anterior cruciate ligament (ACL) are very common, and ACL injuries increase the risk of developing post-traumatic knee osteoarthritis and total knee replacement (TKR). At present, Magnetic Resonance Imaging (MRI) is the most effective imaging modality for distinguishing structural properties of the ACL in relation to adjacent musculoskeletal structures. Several multi-grading scoring systems have been developed to standardize reporting of knee joint abnormalities using MRI including the Whole-Organ Magnetic Resonance Imaging Scale (WORMS) and the Anterior Cruciate Ligament OsteoArthritis Score (ACLOAS). However, both of these grading metrics are susceptible to inter-rater variability. Deep learning methods have recently shown potential to serve as an aid for clinicians with limited time or experience in osteoarthritis grading of the knee menisci and cartilage.

IMAGE: Fang Ren, who developed algorithms to analyze data on the fly while a postdoctoral scholar at SLAC, at a Stanford Synchrotron Radiation Lightsource beamline where the system has been put... view more Blend two or three metals together and you get an alloy that usually looks and acts like a metal, with its atoms arranged in rigid geometric patterns. But once in a while, under just the right conditions, you get something entirely new: a futuristic alloy called metallic glass that's amorphous, with its atoms arranged every which way, much like the atoms of the glass in a window. Its glassy nature makes it stronger and lighter than today's best steel, plus it stands up better to corrosion and wear. Even though metallic glass shows a lot of promise as a protective coating and alternative to steel, only a few thousand of the millions of possible combinations of ingredients have been evaluated over the past 50 years, and only a handful developed to the point that they may become useful. Now a group led by scientists at the Department of Energy's SLAC National Accelerator Laboratory, the National Institute of Standards and Technology (NIST) and Northwestern University has reported a shortcut for discovering and improving metallic glass -- and, by extension, other elusive materials -- at a fraction of the time and cost.