This module was created as a way to get students thinking in new quantitative ways using cutting edge breast cancer research as the context for discovery, letting students experience the utility of math in science first-hand. Students follow along with a simplified but realistic approximation of the original research by reconstructing tissues in 3D to test predictions from a mechanistic agent-based model. There are several quantitative "side trips" that instructors can elect to include/exclude, that expose students to mathematical ideas used to automate image analyses. No prior instructor experience in these topics is assumed or necessary.
Potential Learning Objectives:
- Students will be able to use sums of squares to describe differences.
- Students will use image analysis software to generate data from an image set.
- Students will use image analysis software to generate a 3D data visualization from an image set.
- Students will be able to construct and interpret frequency histograms.
- Students will gain appreciation for the interplay between modeling and empirical work.
- Students will gain appreciation for the utility of mathematics and computation for biology and medicine.
- Students will write a discussion section in typical scientific literature format.
- Students will apply programming concepts to automate a series of procedures.
- Students will quantify aspects of 3D shapes using image analysis.
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