Systems biology is an approach to biomedical research in which scientists combine complex “omics” datasets to develop a more complete understanding of complex biological systems, such as the regulation of whole genome-level transcription, regulation of the 3D genome, the role of signaling and metabolic pathways in disease, and more. Systems biology uses a variety of omics tools including genomics, bioinformatics, metabolomics and proteomics to understand biology at a high level of complexity, such as how mutation or loss of a single gene affects cells, tissues and even the entire organism.

Computational biology is a critical component of systems biology, and in many areas new and improved algorithms are being developed or optimized. These efforts involve the use of computer science, mathematics, and statistics to process and interpret large complex data sets. It provides scientists with the tools to deconstruct these data sets and provide a better understanding of the complexity of normal biological processes and how disruption of those processes leads to a wide range of diseases.