Clinical and experimental trials for new medication can generate complex data, and it’s important to identify which pieces of data are actually relevant. But this becomes difficult when the datasets include millions of genes, metabolites, or other biological factors. PhD candidate Nolan Newman is a computational biologist and uses networks to parse through these datasets and identify which interactions and relationships are important. Put simply – Nolan makes meaning out of chaos. In this episode we dive deep into what systems biology is, why networks are like spaghetti, and how a hearing loss incident prompted Nolan to pursue a career in science.

Hosted by: Bryan & Grace

Check out the ID blog here: https://blogs.oregonstate.edu/inspiration/2022/05/15/spaghetti-networks-oodles-of-nodes/