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.


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.


Social Networks May One Day Diagnose Disease - But At A Cost


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.


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The overarching goal of our Center is to identify the genetic and environmental factors that underlie psychiatric disorders, including autism spectrum disorder, schizophrenia, bipolar disorder, depression, anxiety disorders, and child & adolescent psychopathology. Our team develops and applies drastically new mathematical and computational strategies to infer causal relationships among genetic variation, environmental variables and psychiatric phenotypes.


CSGID applies state-of-the-art high-throughput (HTP) structural biology technologies to experimentally characterize the three dimensional atomic structure of targeted proteins from pathogens in the NIAID Category A-C priority lists and organisms causing emerging and re-emerging infectious diseases.

modENCODE project

The goal of the modENCODE project is to provide the biological research community with a comprehensive encyclopedia of genomic functional elements in the model organisms C. elegans and D. melanogaster. modENCODE is run as a Research Network and the consortium is formed by 11 primary projects, divided between worm and fly, spanning the domains of gene structure, mRNA and ncRNA expression profiling, transcription factor binding sites, histone modifications and replacement, chromatin structure, DNA replication initiation and timing, and copy number variation.

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