The ever-increasing scale and complexity of biological data require advanced computational tools and resources for processing, analyzing, visualizing, and integrating information needed to build, test, and improve predictive models of biological systems. In support of these objectives, ORNL conducts research in the following areas:
ORNL is part of the multi-institutional, multidisciplinary DOE Systems Biology Knowledgebase (KBase) project. KBase is an emerging software and data environment designed to enable researchers to collaboratively generate, test, and share new hypotheses about gene and protein functions; perform large-scale analyses on a scalable computing infrastructure; and model interactions in microbes, plants, and their communities. KBase provides an open, extensible framework for secure sharing of data, tools, and scientific conclusions in predictive and systems biology.
Computational biology activities address fundamental questions in the life sciences and provide information and analytical resources to the wider biological research community by conducting research and development at the intersection of biology, mathematics, information technology, and computational sciences. Interests focus on DNA sequence analysis, gene finding, regulatory regions, and comparative analyses; systems analysis of mRNA and protein expression patterns; databases; visualization; protein structure prediction; protein complexes; pathway and network analysis; modeling and simulation; and high-performance computing.