Computational systems biologist Daniel Jacobsen's group at Oak Ridge National Laboratory is the first to break the exascale barrier and to have done it for biology. At present, this (2.36 Exaops) calculation is the fastest scientific calculation ever done anywhere in the world. This project led to the group's winning the 2018 Gordon Bell Prize - the first ever for systems biology.

Daniel's team focuses on the development and subsequent application of mathematical, statistical, and computational methods to biological datasets in order to yield new insights into complex biological systems. Its approaches include the use of network theory and topology discovery / clustering, wavelet theory, machine & deep learning (among others: iterative random forests, deep neural networks, etc.), and linear algebra (primarily as applied to large-scale multivariate modeling), together with traditional and more advanced computing architectures, such MPI parallelization and Apache Spark.

They make use of various programming languages including C, Python, Perl, Scala and R. Areas of statistics of particular interest to Daniel's lab include the use of both frequentist (parametric and non-parametric) and Bayesian methods, as well as the development of new methods for genome-wide association studies (GWAS) and phenome-wide associations studies (PheWAS). These mathematical and statistical methods are applied to various population and (meta) multiomics data sets (genomics, phylogenomics, transcriptomics, proteomics, metabolomics, microbiomics, viriomics, phytobiomics, chemiomics, etc.), individually as well as in combination, in an attempt to better understand the functional relationships as well as biosynthesis, signaling, transcriptional, translational, degradation, and kinetic regulatory networks at play in biological organisms and communities.