Danh Tran Rose Hills
Generative AI Models to Design De Novo Broad-Host Range Plasmids
Microbiome editing is a new and growing area in machine learning, focused on understanding and controlling how groups of bacteria behave and interact, something that has been hard to study previously. This research could lead to breakthroughs in personalized medicine and the environment.
The Rubin Lab is integrating machine learning into microbiome editing to improve how we understand and change these bacterial communities. We are creating advanced models of bacterial DNA and mobile genetic elements, which will help predict bacterial behavior and make the editing process more efficient. By using advanced ML models to create plasmid sequences, we create molecules that can replicate themselves with targeted bacteria, aiming for precise and effective interventions.
Our approach includes a continuous cycle of experiments that feed information back into the ML models, allowing them to refine and enhance the models over time. This not only makes microbiome editing more capable and broad-ranging, but also deepens our understanding of how microbial communities function, demonstrating the power of machine learning to revolutionize medical treatments.
Message To Sponsor
Thank you very much for your contribution and donation to the Rose Hills Fellowship. Your generosity is extremely important and motivating for aspiring researchers and scientists hoping to make an impact on our world and help our community. More personally, I thank you for allowing me the opportunity to continue my research and realize my curiosity for the duration of the summer term.