摘要Modeling how cells transfer a signal from an extracellular stimulus to different compartments within the cell is critical to understand how different stimuli result in different cellular responses. We designed a software (McSNAC) that proposes a minimal mathematical model to describe biochemical signaling events learning from time-stamped cytometry data. This software makes linear approximations which hold true in many scenarios, but can also break down under several conditions. We explore this approximation in depth to provide guidelines regarding its applicability. In addition, we provide a user interface for non-technical users to analyze their time-stamped cytometry data with this approach.
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