NT908-10 Programming for Biomedical Data Analysis
Introductory description
Computer programming is increasingly essential to the study of all aspects of biology. It is now required for accessing and managing data or performing statistical analyses. This module intends to provide advanced programming skills for students to solve biomedical problems.
The module teaching format will take an active learning, student-centered approach. Classes will consist of introductions to programming techniques and associated biological problems, followed by hands-on exercises.
In summary, this module prepares students for data-intensive research in the biomedical area by teaching data analysis methodology, decision making and computer programming to enable students to become less constrained by limitations of pre-existing computational skills.
Module aims
The module aims to:
- Equip students with computer programming tools and knowledge (e.g.; programming in R) for analysis of systems essentially related to biomedical problems.
- Equip students with analytical and creative skills by developing own code to tackle experimental data.
- To enable students to develop their problem-solving skills, individually and in groups, in particular areas of biomedical research.
Outline syllabus
This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.
Computer programming is done as learning-by-doing. Short lectures are followed by exercises that students attempt by themselves while receiving help from teaching assistants where needed.
- Students will first learn to formulate one-line statements: function calls, named and unnamed parameters, mathematical terms, assignments, variables, plotting.
- Students will be introduced to control structures (if-statements, loops). Training focuses one single-loop programs at first.
- Once students have mastered single-loop programs, the complexity of programs is gradually increased to double-loop programs and multi-loop programs.
- Elements of good programming style are introduced. During the term, four mock exams of increasing length and difficulty are taken and students receive detailed feedback on each mock exam. The mock exams are purely for training and do not form part of the assessment.
Learning outcomes
By the end of the module, students should be able to:
- Understand fundamental programming skills and data analysis
- Develop computer programs to analyse complex biological data
- Critically appraise the quality of large data sets
Indicative reading list
"A First Course in Statistical Programming with R", Braun, Murdoch
http://www.r-tutor.com/r-introduction
View reading list on Talis Aspire
Interdisciplinary
Computer programming is a universal skill to powerfully analyse large data sets of all kinds, and this can be applied to many areas of research such as biology, medicine, chemistry, physics, maths and/or engineering but also social sciences, health sciences or epidemiology. This module's aim is to teach the fundamentals of programming in an interdisciplinary context.
Subject specific skills
-
Key skills:
Ability to creatively go beyond the use of existing tools by writing code.
Critical appraisal of appropriate approaches for a given problem. -
Professional skills:
Use of advanced computational tools to analyse complex biological data.
Develop own computer programs.
Transferable skills
At the end of this module, students will be able to:
- Demonstrate interdisciplinary knowledge
- Critically appraise metholodogy
- Use tools and technology
- Demonstrate creativity and independent thinking as well as adaptability skills
- Demonstrate time-management skills
Study time
Type | Required |
---|---|
Lectures | 10 sessions of 3 hours (30%) |
Tutorials | 8 sessions of 2 hours (16%) |
Private study | 54 hours (54%) |
Total | 100 hours |
Private study description
Self-directed studies: 54 hours that include preparation for next session (e.g.; formative problem-solving exercises)
Students will be advised to dedicate 40% of their time towards the preparation of the sessions and 60% towards the preparation (revision) of the assessed exam.
Costs
No further costs have been identified for this module.
You must pass all assessment components to pass the module.
Assessment group A
Weighting | Study time | Eligible for self-certification | |
---|---|---|---|
Programming Exam | 100% | No | |
Length: 1 X 2 hours written exam based on problem-solving. |
Feedback on assessment
The final exam will be first marked by the Module Lead. The Course Director will moderate marks and individualized feedback in line with WMS assessment criteria (note that due to the nature of coding, plagiarism will not be checked). Feedback will be available to students on request throughout the module, particularly after mock exams. Any student failing the assessment will be offered an appointment with the module lead for face-to-face feedback.
Courses
This module is Core optional for:
- Year 1 of TMDA-B91Z Postgraduate Taught Interdisciplinary Biomedical Research
This module is Option list A for:
- Year 4 of UMDA-CF10 Undergraduate Integrated Natural Sciences (MSci)