Researchers Develop AI-powered Tool Predicts Cell Behaviors

Tuesday, July 30, 2019 - 15:51

Scientists at Helmholtz Zentrum München have developed AI-powered tool that can predict cell behaviors during disease and treatment.

According to an ISCA report, German researchers in cooperation with Mohammad Lotfollahi, have developed a tool that promises to reshape the way we study disease and disease treatment on a cellular level.

Mohammad Lotfollahi, Alex Wolf and Fabian Theis at the Institute of Computational Biology developed scGen, an AI-powered tool for predicting a cell’s behavior in silico, Helmholtz Zentrum München reports.

scGen will help map and study cellular response to disease and treatment beyond experimentally available data. Their work has been published in Nature Methods.

This is a significant step in better understanding cells, tissues and organs in healthy state and provides a reference when diagnosing, monitoring, and treating disease.

scGen is the first tool that predicts cellular response out-of-sample. This means that scGen, if trained on data that capture the effect of perturbations for a given system, is able to make reliable predictions 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, PhD student (Helmholtz Zentrum München and Technische Universität München).

scGen is a generative deep learning model that leverages ideas from image, sequence and language processing, and, for the first time, applies these ideas to model the behavior of a cell in silico. The next step for the team concerns the improving scGen to a fully data-driven formulation, increasing its predictive power to enable the study of combinations of perturbations.

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