scGen, the AI tool, is a generative deep learning model that leverages ideas from image, sequence and language processing and applies them to model the behaviour of a cell performed on a computer or via computer simulation.
As per a study published in the journal Nature Methods, scGen, an Artificial Intelligence (AI)-powered tool, have been developed which is expected to reshape how we study diseases and their treatment at a cellular level.
The AI-powered tool will enable us to map and studying the cellular response to diseases and their treatment beyond experimentally available data. As shown by the researchers, scGen is a generative deep learning model that leverages ideas from image, sequence and language processing and applies them to model the behaviour of a cell performed on a computer or via computer simulation.
Subsequently, scGen will be made fully data-driven in order to increase its predictive power to enable the study of combinations of perturbations. This tool will also help us have the large-scale atlases of organs in a healthy state within the Human Cell Atlas. This is being considered as a major move in understanding cells, tissues and organs in a healthy state in a better way and providing a reference while diagnosing, monitoring and treating diseases.
This AI-driven tool is the first tool that predicts cellular response out-of-sample which implies that if it is trained well on data, it will be able to make bankable forecasts for a different system. "For the first time, we have the opportunity to use data generated in one model system such as mouse and use the data to predict disease or therapy response in human patients," said Mohammad Lotfollahi from the Technical University of Munich.
