Description: Using AI to advance our knowledge of how IDPs function
Using AI to advance our knowledge of how IDPs function
We have new projects looking at the development of machine learning and artificial intelligence (ML/AI) tools for end-to-end biological programming. The project is being supported under the auspices of the US Department of Energy (DOE) Biological and Environmental Research (BER) program and a lab-wide initiative in infusing AI for effective design of biological experiments.
Current lab automation techniques are geared towards optimizing single processes repeatedly and are not well suited for implementing AI-driven experiments. To fully utilize their capabilities in the context of novel, high-throughput biological applications, we need (1) robust programming constructs that can reliably and repeatedly execute experimental protocols, and (2) scalable ML/AI techniques that can automatically capture data, process/analyze, and guide experimental design based on partially available