Programming for Biomedical Informatics
Informatics (INFR11260), Semester 1, 2025
All course materials can be kept up to date by syncing with the course GitHub repository
Applications are now open for the UKRI AI Centre for Doctoral Training in Biomedical Innovation - find out more here
Week 11 Tasks
Tasks for this Week
In our final revision session on Tuesday, we will run through the exam structure, course content, some example short answer questions and review how you structure pseudo-code with suitable commenting using some practical examples.
Please do use this time to ask any questions you may have, but we will also be monitoring the Piazza forum right up until the exam so you can as usual ask questions there too.
Remember you can download last year’s exam here to give you a concrete example of the question style.
A key tip for the exam is to pay attention to how many marks a part is worth and apportion your time appropriately.
Remember that I’ve added some reading and reference material suggestions that some of you may like to refer to for some background biology information. This is entirely optional, you are not expected to read through all these, but may find them useful on occassion during the course. You can find these here.
In this course, you will learn how to use Python to retrieve and parse data from biological repositories through bulk download and application programming interfaces (APIs). You will learn about established data formats for different data modalities so that you can understand the structure and content of the data and how it was generated. Each week we will focus on analytical tasks in linked topics that span the main components of modern biomedical informatics research. Topics will change slightly each year, but will typically include tools, algorithms, and approaches for biological sequence, multi-omics (transcriptomics, proteomics, methylomics), biomedical network, and biomedical text analysis. Each topic will be explored using real-world examples.
On successful completion of this course, you should be able to:
- select sources of biomedical data appropriate for a given research question.
- determine the most suitable methods to use to analyse these data.
- implement and critically evaluate advanced Python code for biomedical data projects using reproducible research practices.