Large-scale calibration and simulation of COVID-19 epidemiologic scenarios to support healthcare planning.

The COVID-19 pandemic has provided stiff challenges for planning and resourcing in health services in the UK and worldwide. Epidemiological models can provide simulations of how infectious disease might progress in a population given certain parameters. We adapted an agent-based model of COVID-19 to inform planning and decision-making within a healthcare setting, and created a software framework that automates processes for calibrating the model parameters to health data and allows the model to be run at national population scale on National Health Service (NHS) infrastructure.

Using Semantic Web Technologies to Enable Cancer Genomics Discovery at Petabyte Scale.

Increased efforts in cancer genomics research and bioinformatics are producing tremendous amounts of data. These data are diverse in origin, format, and content. As the amount of available sequencing data increase, technologies that make them discoverable and usable are critically needed.

The Cancer Genomics Cloud: Collaborative, Reproducible, and Democratized-A New Paradigm in Large-Scale Computational Research.

The Seven Bridges Cancer Genomics Cloud (CGC; www.cancergenomicscloud.org) enables researchers to rapidly access and collaborate on massive public cancer genomic datasets, including The Cancer Genome Atlas.