The class is organized around the understanding of 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 teach graduate students how to reason quantitatively in the biosciences given uncertainty in mechanisms, rates and reliability of measurements.