Physical Biology of the Cell @ NCBS
About
This intensive week long mini-course explores the way that physical and mathematical models can be used to understand biological systems. The course begins by examining the way in which simple order of magnitude estimates can be used to provide insights into problems ranging from the fidelity of protein translation to how far a bird can fly without stopping to how amphibians arrive on oceanic islands. This is followed by the use of statistical mechanics to explore problems in regulatory biology. Some examples include the physics of post-translational modifications, how cells make transcriptional decisions and the precision with which embryonic development takes place. In addition to these topics, the course also involves a series of hands-on projects using Python to amplify the case studies discussed in class.
Where and When?
The course will take place from 14 January through 18 January 2019.
Syllabus
| Date | Topics |
|---|---|
| 14 Jan. | A feeling for the organism. |
| We will test our biological intuition and use the principles of “street-fighting mathematics” to make testable estimates about biological phenomena. | |
| 15 Jan. | Diffusive dynamics and explorations in probability. |
| Diffusion is biology’s null model of molecular motion. We will explore the dynamics and consequences of diffusion through a mathematical lens and it’s deep connection to probability | |
| 16 Jan. | Life as an Elephant - our next adventure in probabilistic biology. |
| We will think of a variety of biological processes as input-output functions. From ion channels to transcription factors, thermodynamics and statistical mechanics can be used to understand cellular physiology. | |
| 17 Jan. | Equilibrium and Disequilibrium. |
| We will continue our discussion of equilibrium models in biology and emphasize the utility of flux and balance laws. | |
| 18 Jan. | Conservation, continuum, fluxes, dynamics & concluding thoughts on Physical Biology |
| We’ll continue on the huge topic of how systems change over time. We’ll wrap up the course with a celebration of quantitative biology by examining success stories. |