Computing challenges and systems biology

Abstract

Over the past two decades the manner in which science is conducted in biology and related disciplines has been changing dramatically. Automation has led to a vast amount of data being generated by new experimental techniques, such as genomic sequencing and DNA microarrays. To extract the scientific insights buried in this high volume of data, life science researchers are employing increasingly sophisticated information technology approaches to create data analysis and simulation tools that run on high performance computing (HPC) platforms. The domain is one rich in compute-intensive applications: determining gene sequence, predicting macromolecular structure, understanding the temporal dynamics of protein folding, modeling molecular interactions, simulating the behavior of cell-signaling cascades and genetic regulatory networks, and the real-time manipulation of 3D rendered volumes of organs derived from structural magnetic resonance imaging scans. Future trends in the life sciences are expected to expand upon this set to include computation performed using hybrid bio-nano devices, personalized medicine, mining of heterogeneous data sets stored at disparate sites, and knowledge discovery in patient medical records. The talk will review high performance computing needs in emerging systems biology applications, the potential impact of bio-nano research on future high performance computing designs, and work on related topics at DARPA.