Predictive Biology: Learning from Data in Microbiomes

Undergraduate / Graduate

In the 21st century, biology is completing its transition from a descriptive discipline to a predictive science. At the heart of this transformation is an essential craft: the ability to translate massive datasets into biological understanding. This course prepares advanced undergraduates to lead this shift, mastering the computational tools required to decode the logic of complex biological systems. We will bridge the gap between measurements and models by coarse-graining biological complexity-leveraging neural networks and non-linear dimension reduction to distill simplified descriptions from high-dimensional data. Rather than getting lost in microscopic detail, you will learn to construct effective models that capture the core principles governing biological dynamics. We will utilize AI-assisted coding to bypass syntax hurdles, allowing us to focus on the principled evaluation and critical interpretation of our results. While these methods apply across all scales-from proteins to ecosystems-we will master them in the context of the microbiome. From the human gut to the soil, microbes form communities of staggering complexity that drive global nutrient cycles and human health. By exploiting high-dimensional sequencing and metabolite measurements, you will join a multidisciplinary frontier, learning to distill clear, predictive insight from the beautiful chaos of data.