The practice of programming 1100-3BB15
1. Review of Python basics.
2. Introduction to data analysis using pandas.
3. Plots in matplotlib and seaborn.
4. Introduction to Biopython.
5. Integration of PyMOL with Python.
6. Analysis of molecular dynamics trajectories with MDAnalysis.
7. Other packages useful for data processing in biophysics.
Type of course
Prerequisites (description)
Course coordinators
Learning outcomes
Upon completing the course, the student has a fundamental understanding of programming in Python and data analysis using libraries such as pandas, matplotlib, and seaborn. They are familiar with bioinformatics tools like Biopython and can integrate PyMOL with Python. The student is capable of analyzing biophysical data using the specialized Python modules discussed during the course.
Assessment criteria
Grading criteria:
- Up to two unexcused absences are allowed.
- Active participation in class and completion of homework assignments.
- Final project and a discussion about the project (final exam).
The final grade will be based on points earned from class participation (40%) and the final project with its discussion (60%).
Bibliography
The student will receive the necessary materials during the course.
Additional resources:
Python Documentation
Python Tutorial
Python Programming for the Absolute Beginner, Michael Dawson
Learning Python, Mark Lutz
Python Pocket Reference, Mark Lutz
Practice Python - Exercises
Additional information
Information on level of this course, year of study and semester when the course unit is delivered, types and amount of class hours - can be found in course structure diagrams of apropriate study programmes. This course is related to the following study programmes:
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: