Computing and Biology: Toward Predictive Theory in the Life Sciences
SESSION: Genomics-Driven Biology
EVENT TYPE: Masterworks
TIME: 3:30PM - 4:15PM
SESSION CHAIR: Michelle Butler
ABSTRACT: Advances in genome sequencing have made it possible to sequence over 1,000 species, and during the next 5-10 years it should become routine to sequence humans as part of medical diagnostics and to sequence thousands more organisms important to energy, industry, and science. Genome analysis methods powered by petascale systems will make it possible to quickly go from DNA sequence to functional knowledge and predictive models. Making this a real-time process will radically change the uses of genomic sequencing data. Uncovering individual gene history and protein families will reveal the factors that influence molecular evolution, refine our strategies for databases of protein structures, and lay the foundation for understanding the role of horizontal gene transfer in evolution. Mathematical techniques and large-scale computing are revealing how to reconstruct cell networks, map them from one organism to another, and ultimately develop predictive models to shed light on evolution, ecosystems, development, and disease.
Michelle Butler (Chair) - National Center for Supercomputing Applications
Rick Stevens - Argonne National Laboratory / University of Chicago