ASCB EMBO 2017 Poster: A machine learning framework for kinetic phenotypic prediction of neurologica
- Dec 6, 2017
- 1 min read
The results presented in this poster provide a strong evidence of analyzing dynamic molecular events using time-lapse microscopy for discovering the pathogenic mechanisms underlying disease phenotypes. We will multiplex additional biomolecular reporters for spatial-temporal functional dynamics and cell fate readouts in the future. For more information see full size poster.
James Lee was the poster presenter at ASCB EMBO 2017.
To try Aivia: https://www.drvtechnologies.com/demo
