PNNL researchers developed a new computational workflow to study day-to-night gene expression dynamics of cyanobacterium in real time.

Predicting how organisms’ characteristics respond to not only their genes, but also their environments (a nascent field called predictive phenomics), is extraordinarily challenging. Researchers at PNNL are using AI to tackle that challenge.

PNNL chemical engineer Mariefel Olarte shares passion for mentoring students and the next-generation workforce.

Three PNNL researchers will receive five continuous years of funding for projects through highly competitive DOE Early Career Research Program awards.