We developed an easy-to-use GUI software in tele sleep score to automatically score sleep stages in mice. We aim to address the challenge of labor-intensive manual scoring and improve accessibility for researchers without much coding experience. In tele sleep score achieves 95.2%accuracy in automatically scoring sleep stages in mice and proved generalizability on two other publicly-available independent data sets.
The GUI includes a manual correction feature, allowing users to modify the scored sleep stage for any epoch. We also provide ASAP value visualizations to explain the model scoring decisions. Experienced users can also fine tune our pre-tree model with their own data as all necessary files and extraction scripts are available on GitHub.
Our research focuses on translating emerging genetics into biology and enabling next-generation therapeutics to treat psychiatric illnesses. We have been working on genes whose dysfunction has been implicated on these illnesses using molecular, cellular, and electrophysiological approaches, both in vitro and in animals.
