PHYSCI M178
Quantitative Regulatory Biology and Signal Transduction
Description: (Formerly numbered 178.) (Same as Computational and Systems Biology M178 and Microbiology M178.) Lecture, three hours; laboratory, one hour. Requisites: Life Sciences 7A, 7B, 7C, 30A, 30B. Introduction to key biological regulatory circuit motifs and systems biology concepts that are critical to understanding how cellular responses are controlled. Letter grading.
Units: 4.0
Units: 4.0
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Most Helpful Review
Fall 2025 - This was an amazing class. Many PhySci majors take this class expecting for it to be very easy, and are surprised when the topics are mildly difficult and require work. While this was not an easy class on an absolute scale, relative to other upper division PHYSCI/MIMG/CaSB courses, it was very easy. It was by far one of the most rewarding I have taken at UCLA. There is a precedent set that you can learn nothing, and still come out with an A, but if you're willing to put in the work, then this class will be incredibly rewarding and helpful for your research. The problem sets are very manageable as long as you don't wait until the night before to start them, and the lowest grade is dropped. The final project can be as easy or as difficult as you want to make it. This class is very easy to end with an A on. As long as you have a baseline knowledge of python (in other words, if you took LS 30A/B), then you will have all of the coding knowledge that you'll ever need. I recommend every person with even a partial interest in computational biology to take this course.
Fall 2025 - This was an amazing class. Many PhySci majors take this class expecting for it to be very easy, and are surprised when the topics are mildly difficult and require work. While this was not an easy class on an absolute scale, relative to other upper division PHYSCI/MIMG/CaSB courses, it was very easy. It was by far one of the most rewarding I have taken at UCLA. There is a precedent set that you can learn nothing, and still come out with an A, but if you're willing to put in the work, then this class will be incredibly rewarding and helpful for your research. The problem sets are very manageable as long as you don't wait until the night before to start them, and the lowest grade is dropped. The final project can be as easy or as difficult as you want to make it. This class is very easy to end with an A on. As long as you have a baseline knowledge of python (in other words, if you took LS 30A/B), then you will have all of the coding knowledge that you'll ever need. I recommend every person with even a partial interest in computational biology to take this course.
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