University of Maryland, Spring 2025

BIOL706 explores how living systems operate—from the scale of single cells to entire populations—through the application of quantitative principles. Students will learn to connect biological mechanisms with computational models and experimental data. By the end of this class, students should be able to:

• Understand quantitative principles of how living systems work; Approaches for building and evaluating models of biological processes;
• Explore key concepts in practice through computational modules in Python, R, and MATLAB.

The course is designed to help students from physics, engineering, mathematics, computing, and the life sciences translate classroom learning into practical research skills, bridging disciplines to tackle complex problems in modern biology.

Foundations in Quantitative Biosciences

Georgia Institute of Technology, Fall 2016/17/18/19/20

The class is organized around understanding key advances in the biosciences, one organizing unit at a time, in which the advances depended critically on quantitative methods and reasoning. Both foundational advances and recent challenges will be discussed. Each week, students will be exposed to:

• Methods for developing and analyzing quantitative models;
• Logic for how to reason given uncertainty in the biosciences;
• Computational skills to implement and support a thorough understanding of stochastic and dynamic modeling at the interface between mathematical formalism and biological data.

The overall objective of the course is to train graduate students how to reason quantitatively in the biosciences given uncertainty in mechanisms, rates and reliability of measurements.