Biochemical reactions relevant for life involve a large number of species and occur over a range of spatial and temporal scales. Such systems are often difficult to analyze and prohibitively expensive to simulate. However, understanding such reactions is central to understanding how organisms function in health and disease. Different analytical and computational techniques have thus been developed to make their mathematical and computational study tractable, ranging from quasi-state-state approximations of chemical master equation to hybrid computational methods.  This satellite meeting will focus on recent developments in the inference, analysis, modeling of biochemical reactions.  Of particular interest will be stochastic methods applied to reactions that evolve on different scales, e.g. on the spatial scales ranging from cells to tissue, and temporal scales ranging from those of within cellular transport to cell division times. 

Recent technological advances (e.g., GFP, luciferase, wearable device, etc) continue to make the acquisition of time-series data easier. Such data has allowed for unprecedented insights into the dynamics of biological processes across scale. The  meeting will also focus on the methods of analysis for such time-series data, especially when such inference goes hand-in-hand with identifying the biological mechanisms driving the dynamics, and model identification.