@article {Dale2022.01.20.477155, author = {Renee Dale and Stewart Craig}, title = {Integrating Math Modeling, Coding, and Biology in a CURE Lab}, elocation-id = {2022.01.20.477155}, year = {2022}, doi = {10.1101/2022.01.20.477155}, publisher = {Cold Spring Harbor Laboratory}, abstract = {The development of mathematical and quantitative skills is increasingly critical for biology students. Literacy in coding, statistics, and mathematical modeling enables students to engage in systems-thinking and the analysis of large data sets. Here we present a flexible tool illustrating concepts in mathematical modeling, coding, and biology for integration into both traditional {\textquoteleft}cookbook{\textquoteright} and inquiry-driven labs for freshmen biology students. We developed simple and complex mathematical models of potato catechol oxidase, a popular system to teach enzyme kinetics in undergraduate biology labs. We integrated both models into a freely-available web app for simulation and parameter estimation. The models are usable even if experimental details are unknown or poorly controlled, so that even novice students can work through the problem. We illustrate this by estimating the kinetic parameters of catechol oxidase in the complex model using data obtained from two sections of a course-based undergraduate research experience (CURE) freshman biology lab. Worksheets with questions motivating model building and simulation comprehension are provided. The effect of these exercises on students{\textquoteright} opinions of math, biology, and coding are evaluated using pre- and post-test surveys and student feedback. Our results show that these tools illustrate enzyme kinetics mathematically, students are not intimidated by the degree of math or coding involved, and in some cases are interested to do more, despite being unaware of the focus of the lab when signing up.Competing Interest StatementThe authors have declared no competing interest.}, URL = {https://www.biorxiv.org/content/early/2022/01/24/2022.01.20.477155}, eprint = {https://www.biorxiv.org/content/early/2022/01/24/2022.01.20.477155.full.pdf}, journal = {bioRxiv} }