AQuA (Astrocyte Quantification and Analysis) is an effective tool to detect signaling events from microscopic time-lapse imaging data of astrocytes or other cell types. The algorithm, developed by Guoqiang Yu’s group at Virginia Tech, is data-driven and based on machine learning principles and can be applied across model organisms, fluorescent indicators, experimental modalities, cell types, and imaging parameters.
More information about AQuA: https://github.com/yu-lab-vt/AQuA
A prototype for a web-based service version of AQuA is also under development. Please stay tuned!