Throughout the course, we will break out of the lecture to explore concepts more thoroughly through computational analysis. We’ll write a wide variety of code covering concepts such as mathematical techniques, stochastic simulations, and image processing. Furthermore, we will work through an experimental data set to quantify gene expression in bacterial cells.

Introductory Materials

Please work through the following tutorials before the beginning of class. The TAs will hold a special session covering these topics on Sunday, January 20th from 16:00 to 17:00 in College A.227. Note: In some browsers (Firefox primarily), the end of each sentence is clipped off, making it difficult to read. If this is occurring, please try using another browser (Chrome, Safari, etc).

Data sets

Please download the following data sets, unzip them, and place them in your bootcamp/data folder as described in the setting up Python tutorial.

  • Data Set 1 | A series of phase contrast and fluorescence images of a growing E. coli colony

  • Data Set 2 | A large image set of E. coli strains with varying copy numbers of the lacI repressor molecule.

Python Utilities

As sometimes syntax can be difficult, we have written a file with a few functions written in Python that will make some of the in-class exercises less cumbersome. Please download them below and place them in your root bootcamp folder as described in the setting up Python tutorial: | Course utilities.

Course Exercises

As we go through the course, the code we write in class will be posted here. When possible, extra tutorials with more detail and explanation will be posted as well.