Selected Topics in Programming for Life Scientists

The course is a 12-part course, with 1.5 hrs class work and about 1.5 hrs of practice work per class. The course will also include a self-assigned project which will be evaluated in addition to the weekly homework. It is geared at life scientists at any career stage. Examples will be taken from a selection of topics such as behavior, electrophysiology, bioinformatics, immunostaining, etc. The course will be hands-on, will use life science examples, and use Python programming. This course aims to develop code independently to solve tasks you may encounter in your research. An example scenario would be to write a program that could address: 'It would be great if I could quickly count the number of cells in this slice.'

COURSE PLAN
1. Why programming/ writing scripts in Python/ loading and manipulating data/variables / plotting-1
2. Functions/syntax/testing and documenting/function default / seeking help / plotting-2
3. Lists and loops
4. Conditionals / building a guessing game
5. Detecting a sphere in a dark image
6. Spreadsheets / reading .mat files
7. Grid cells example / plotting-3
8. String manipulation / mRNA -> protein and vice versa /python pickle
9. Tracking mice in an open field
10. Counting cells in an immunostaining
11. Estimating the growth rate of a plant root from images
12. Discussing self-assignments and feedback

Target group: Anyone with a life sciences background and keen to use programming in their workflow.
This is not software support for your research.
Auditing is discouraged. You learn by practicing to write code.

Prerequisites: A working laptop.

Evaluation: Homework assignments after each class (60%) and a self-assigned project (40%). 70% is pass. Auditing is discouraged. a) The assignments are evaluated for their attempt. b) A self-assigned project that utilizes programming should be proposed before the midterm. This can be any project of your choice, preferably within the scope of scientific research. The proposal will be screened for its adequacy and feasibility in the time frame of this course and any further recommendations will be suggested. The grading for this is scaled based on individual skill levels.

Teaching format: This is offered as an in-person course and will not be held online. Each participant works on their computer while following instructions, with assistance from the TA.

ECTS: 3 Year: 2024

Track segment(s):
Elective

Teacher(s):
Andrea Navas Olive Chaitanya Chintaluri

Teaching assistant(s):
Ivan Bulygin