Machine learning has a variety of applications in scientific research, from rapidly analyzing datasets to making predictions. At the Joint BioEnergy Institute (JBEI), researchers are using machine learning to find new proteins that play a role in plant gene expression — providing the scientific community with new avenues to explore in bioenergy crop engineering.
Making Sustainable Products Faster with AI and Automation
Héctor García Martín, a staff scientist in the Biological and Systems Engineering (BSE) Division, is working to accelerate and refine the synthetic biology landscape by applying artificial intelligence and the mathematical tools he mastered during his training as a physicist.
Using Biology to Make Vaccine Adjuvants More Available
Biosciences Area Senior Faculty Researcher Jay Keasling and his research team have spent the past few decades engineering yeast to be tiny factories that more efficiently produce molecules that are typically found in small supply in nature. Now, they have modified yeast to make the adjuvant QS-21, an important additive to vaccines that stimulates the … Read more »
Cracking Sugarcane’s Genetic Code
Scientists created a highly accurate reference genome for one of the most important modern crops and found a rare example of how genes confer disease resistance in plants. Exploring sugarcane’s genetic code could help researchers develop more resilient and productive crops, with implications for both sugar production and biofuels
Is Mold the Future of Food?
Chef-turned-bioengineer Vayu Hill-Maini is modifying the genes already present in fungi to create innovative new foods that are tasty, healthy, and more environmentally sustainable.
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