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Curricular information is subject to change
At the end of the module, students should be able to:
- Configure and setup python IDE for life science projects
- Write basic functional python scripts
- Identify packages and libraries essential to scientific computing
- Write python codes for the following indicative applications including motif identification in genomic data, pattern identification in interaction network data, and dynamic modelling of biochemical switches.
Python basics - getting started with "how-to-program" using Python.
Advanced Python - covering object-oriented, regular expressions, calling libraries and packages for life science application
Students will work on specific examples covering simple biochemical calculations and sequence analysis, to modelling the dynamic interactions of genes and protein in cells and evolutionary properties of system biology. How-to implementation using projects in Python.
Student Effort Type | Hours |
---|---|
Lectures | 12 |
Specified Learning Activities | 50 |
Autonomous Student Learning | 50 |
Total | 112 |
Not applicable to this module.
Description | Timing | Component Scale | % of Final Grade | ||
---|---|---|---|---|---|
Continuous Assessment: Two programming challenges to evaluate the programming competency: Basic Python covering Week 1- 4 (25%) and Advanced Python covering Week 5- 8 (25%). |
Throughout the Trimester | n/a | Standard conversion grade scale 40% | No | 50 |
Project: Python scripting for life science application (50%) -- students will complete a skeleton Python project | Throughout the Trimester | n/a | Standard conversion grade scale 40% | No | 50 |
Resit In | Terminal Exam |
---|---|
Spring | No |
• Feedback individually to students, on an activity or draft prior to summative assessment
• Feedback individually to students, post-assessment
Not yet recorded.
Name | Role |
---|---|
Professor Brendan Loftus | Lecturer / Co-Lecturer |