Handling, Analysis, and Storage of Big Data for Healthcare

Advances in experimental science and technology are extending the limits of the resolution, scale, and throughput of data that can be acquired. This creates significant data handling and analysis issues. We develop automated data processing pipelines in MATLAB^® to remove manual steps and parallelize processing. Removing these challenges enables us to process large volumes of data from the Rosetta CRUK Grand Challenge Project in order to understand the cancer and tumor microenvironment.