Computational Biology, Programming and Practice
| Code | School | Level | Credits | Semesters |
| LIFE4138 | Life Sciences | 4 | 20 | Autumn UK |
- Code
- LIFE4138
- School
- Life Sciences
- Level
- 4
- Credits
- 20
- Semesters
- Autumn UK
Summary
In this module students will develop basic command line skills in Unix to manipulate large data file types commonly used in bioinformatics. Students will also learn how to run scripts from others as well as write and develop their own. The module will cover python and R scripting and provide students with the tools to develop their own code in future. Students will work within interactive coding environments to generate figures and maintain reproducibility in code and practice. By the end of the module, students will be equipped with the practical skills to write simple code to address biological problems.
Target Students
This module is only available for students on the MSc Bioinformatics.
Classes
This module may be delivered through lectures, seminars, workshops and labs etc
Assessment
- 25% Inclass Exam 1 (Practical): In class exam assessing material learned in weeks 1 and 2. Students will be allowed access to teaching materials and may be able to use online resources to efficiently solve problems. Students will be assessed on the ability of the code they provide to answer specific biological questions.
- 75% Coursework 1: Coursework coding challenge assessing material learned in weeks 3 and 4. Students will be assessed on the ability of the code they provide to answer specific biological questions.
Assessed by end of autumn semester
Educational Aims
This module will introduce the fundamental concepts of programming and data manipulation to students without significant prior experience of the command line. Participants will learn how to write simple code in an interactive environment. Weekly sessions will introduce fundamental programming concepts and approaches. Participants will then have sessions of self-directed learning to practice and develop the skills required to complete a series of programming challenges.Learning Outcomes
• Knowledge of the unix environment, command line operations and simple command line scripting.
• Knowledge of online sources of information and guidance for solving common problems in computational biology.
• The ability to install and run scripts within an appropriate environment and install necessary co-requisites.
• Fundamental skills in an interpreted programming language suitable for manipulation of biological data (namely Python).
• The ability to manipulate and analyse data using a statistical scripting environment (namely R).
• How to use libraries and packages to solve common problems in programming.
• How to use environments (virtual and Conda based) and package managers to simplify code portability.
• Knowledge of typical biological data file formats and the ability to write new files or edit existing files in place.
• The ability to write simple scripts, employ the concepts of class-oriented programming and develop simple applications to reproducibly solve common problems.
• The ability to use tools such as GIT, Jupyter notebooks and R Markdown documents to facilitate reproducible and shareable code.
• How to carry out code review and satisfactorily comment and optimise code.
• Basic approaches to packaging and distributing code.
• The ability to link and extract data from external resources.
• How to use scripts to interact and control other programs and extract results from them.