Open source tools and standardized data in cancer systems biology

Abstract

To reach the full potential of multicellular systems biology, mathematical and computational modelers must pool their efforts to share and curate biophysical measurements, create and combine mathematical models, analyze and visualize model predictions, and validate and refine against shared data. An ecosystem of open source software that reads standardized data is essential. We review the state-of-the-art in open source software and data standards in multicellular systems biology, and point out areas of needed growth to move beyond isolated models to community-driven frameworks that shed light on complex problems in multicellular systems biology.