C&S BIO M150
Biological Modeling: Mathematical and Computational Approaches
Description: (Same as Ecology and Evolutionary Biology M159.) Lecture, four hours; laboratory, three hours. Requisites: Life Sciences 7A, 7B, 7C, Mathematics 33A and 33B, with grades of C or better. Recommended Requisites: Physics 1A, 1B, and 1C, or 5A, 5B, and 5C, with grades of C or better. Students learn how to translate their biological knowledge and intuition into mathematical equations and computer simulations, and how to interpret and glean biological insights from quantitative results and predictions. Review and integration of core mathematical and computational approaches in novel ways. Students gain experience translating and intuition about systems through many examples across range of biological levels, such as predator-prey, disease transmission, cancer initiation, cell migration, neural systems, vascular networks, sleep, drug interactions, gene expression, and more. Students learn how to manipulate data, basics of coding, and how to instantiate their mathematical models and biological intuition through numerical solutions and simulations. Letter grading.
Units: 5.0
Units: 5.0
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Most Helpful Review
Spring 2025 - Overall, this is definitely the hardest class in the C&S Bio methodology series. It integrates all the concepts learned in lower division classes and expects you to know some modeling concepts, too. However, the class is easy in the sense that (1) no attendance is required, ever (2) problem sets are worth more than the final and midterm (and they are only 10%), and (3) the professor encourages collaboration; he wants people to do well. Although the material was dry and unclear at times, having friends in this class is all you need to do well. Definitely feel like I learned a lot and about some foundational biological modeling concepts.
Spring 2025 - Overall, this is definitely the hardest class in the C&S Bio methodology series. It integrates all the concepts learned in lower division classes and expects you to know some modeling concepts, too. However, the class is easy in the sense that (1) no attendance is required, ever (2) problem sets are worth more than the final and midterm (and they are only 10%), and (3) the professor encourages collaboration; he wants people to do well. Although the material was dry and unclear at times, having friends in this class is all you need to do well. Definitely feel like I learned a lot and about some foundational biological modeling concepts.
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