Visualization: Quantitative reasoning via image analysis, networks, topology, generative models, and 3D rendering
Author(s): Sam S Donovan1, John R Jungck2
1. University of Pittsburgh 2. Interdisciplinary Science Learning Center at the University of Delaware
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Description
Additional resources for:
"Visualization: Quantitative reasoning via image analysis, networks, topology, generative models, and 3D rendering" by John R. Jungck
Date and Time: Sunday, June 14 @ 10:30AM
Description: In this workshop, I will focus on ten different kinds of hypothesis testing via mathematical analysis of visuals in biology: (1) Phenomenological; (2) Topological; (3) Geometric; (4) Spatial Statistics; (5) Networks; (6) Iterative Fractal Generation; (7) Fractal Measurement; (7) Bioorthogonal Transformations: Warping, Morphing, Morphometrics, Landmarks; (8) Cellular Automata; (9) 3D rendering; and (10) Hyperbolic space. In each case, I argue that visual representations are testable hypotheses, help us reason about biological causation, and help us communicate our inferences. For students to be empowered as scientific investigators, I argue that they need more visual tools than linear regression of an X-Y scatterplot of points or a histographic display of frequencies or compositions.
Software:
- ImageJ -a public domain, Java-based image processing program
- FracLac - plugin for ImageJ
- Ka-Me - a Voronoi image analyzer
- 3D Fractal Tree Calculator
- BioCALab
Handouts:
Labs
- 3D FractaL-Tree
- Biological Cellular Automata Lab
- Modeling More Mold [zip file: 4.84 MB]*
- Shaped to Survive[zip file: 982 KB]*
- Valuing Variegated Variation[zip file: 2.07 MB]*
*Note: You will need to be logged into your QUBES account to access zip files.
Literature:
- Jungck, J.R. & R. Viswanathan. 2015. Graph theory for systems biology: interval graphs, motifs, and pattern recognition. In: Robeva, R. (eds.) Algebraic and Discrete Mathematical Methods for Modern Biology, Burlington: Academic Press, 2015, pp. 1-27. (link to publisher website)
- Author copy available by special request if book is unavailable at your institution's library
- Khiripet, N., W. Khantuwan, & J.R. Jungck. 2012. Ka-me: a Voronoi image analyzer. Bioinformatics 28:1802-1804. (link to pdf)
- Khiripet, N., R. Viruchpintu, J. Maneewattanapluk, J. Spangenberg, & J.R. Jungck. 2011. Morphospace: measurement, modeling, mathematics, and meaning. Math. Model. Nat. Phenom. 6:54-81. (link to pdf)
Cite this work
Researchers should cite this work as follows:
- Donovan, S. S., Jungck, J. R. (2018). Visualization: Quantitative reasoning via image analysis, networks, topology, generative models, and 3D rendering. BioQUEST / HHMI / CaseNet Summer Workshop 2015, QUBES Educational Resources. doi:10.25334/Q4W39V