09
Aug
2017

Veterans will be the ultimate winners in the U.S. Department of Veterans Affairs-Department of Energy (DOE) Big Data Science Initiative, a collaborative research effort that casts Argonne National Laboratory in a prominent role. Argonne’s extensive track record of successes with big data and big computers make it the quintessential partner of this multi-faceted research team to improve healthcare for millions of veterans, advance supercomputing and solve some of the nation’s biggest scientific challenges. A team led by the Computation Institute's Rick Stevens, associate laboratory director for Computing, Environment and Life Sciences at Argonne, was instrumental in moving the effort from concept to reality.

26
Jul
2017

A new mathematical model of ecology created by University of Chicago scientists provides the most accurate reproduction to date of natural biodiversity, according to a new paper in the journal Nature. For almost a century, ecologists have conceptualized an ecosystem as the sum of pairwise interactions, such as predator and prey, herbivore and plant, or parasite and host. However, equations based on that theory failed to replicate the diversity and resilience of natural ecosystems. Building upon previous work that modeled competition between species as similar to a game of rock/paper/scissors, a team led by Stefano Allesina, Professor of Ecology & Evolution at the University of Chicago, found that adding additional competitors could generate stable and robust model ecosystems.

29
Jun
2017

As social networks, apps, and other websites become more adept at turning user data into personalized experiences, more frequent stories appear that highlight the exciting -- and sometimes disturbing -- implications of that technology for health.

19
May
2017

Two groups of Computation Institute researchers at the U.S. Department of Energy's (DOE) Argonne National Laboratory earned special awards from the office of the U.S. Secretary of Energy for addressing the global health challenges of Ebola and cancer.

04
May
2017

An international team of scientists including the Computation Institute has determined the 3-D atomic structures of more than 1,000 proteins that are potential targets for drugs and vaccines to combat some of the world’s most dangerous emerging and re-emerging infectious diseases.

01
May
2017

People have touted the potential of big data and computation in medicine for what feels like decades, promising more effective and personalized treatments, new research discoveries, and smarter clinical predictions. But only recently have these technologies made it to the clinic where they can actually improve patient care. At University of Chicago Medicine, several collaborations between physicians, researchers, and computational experts have produced such pioneering applications, from the pathology lab to the critical care wards.

09
Mar
2017

As more researchers turn to whole genome sequencing, the data challenges increase.  A new $1.58 million award from the National Institutes of Health equips Globus Genomics to develop new tools and services that help geneticists overcome these obstacles and unlock new discoveries.

03
Jan
2017

Using the University of Chicago Medicine data warehouse, a team led by CI faculty and fellow Samuel Volchenboum detected a dangerous ripple effect in hospitals: when one patient becomes critically ill, chances of a similar setback increase for others in the same unit.

28
Jun
2016

Given its expeditionary namesake, it's only appropriate that Beagle -- the University of Chicago's supercomputer for biomedical research -- works with data from all around the world. But a recent project may qualify as the farthest-traveling data yet, as the HPC resource was used in a new genomic study of populations living in the Himalayan mountain range. 

17
Mar
2016

As interest in artificial intelligence gains mainstream traction, computers and brains are increasingly compared to each other. But despite great advances in computer architecture and software, even the world’s most powerful computers can’t compete with the efficiency of the human brain. Capable of processing a constant flood of sensory information and make snap decisions, the brain nevertheless only burns about 15 watts of energy, less than a common light bulb.