IFN646 Biomedical Data Science
To view more information for this unit, select Unit Outline from the list below. Please note the teaching period for which the Unit Outline is relevant.
| Unit code: | IFN646 |
|---|---|
| Prerequisite(s): | ((IFN580 or IFN509 or IFQ509) OR (192cps in IV04) OR (admission into IV54) OR (192 cps in LV41 and admission into LV41) |
| Credit points: | 12 |
| Timetable | Details in HiQ, if available |
| Availabilities |
|
| CSP student contribution | $1,164 |
| Domestic tuition unit fee | $3,816 |
| International unit fee | $5,352 |
Unit Outline: Semester 2 2025, Gardens Point, Internal
| Unit code: | IFN646 |
|---|---|
| Credit points: | 12 |
| Pre-requisite: | ((IFN580 or IFN509 or IFQ509) OR (192cps in IV04) OR (admission into IV54) OR (192 cps in LV41 and admission into LV41) |
| Coordinator: | Dimitri Perrin | dimitri.perrin@qut.edu.au |
Overview
Biology and medicine are becoming data-intensive disciplines. From new sequencing technologies to electronic health records and wearable devices, it has never been easier or cheaper to generate biomedical data. This provides a great opportunity to study complex biological systems, to offer better patient care, etc., but working with this data is not trivial. This advanced unit will teach you how to handle and analyse biomedical data, as well as gain an appreciation of its strengths, limitations and complexities so that you can understand and critically interpret measurements and analyses. The unit aims to provide you with knowledge of modern biomedical technologies and the associated data science methodologies, building on what you have learned in IFN509.
Learning Outcomes
On successful completion of this unit you will be able to:
- Discuss biomedical technologies and their suitability for specific applications.
- Analyse complex biomedical data using appropriate methodologies and tools, and implement data analysis pipelines
- Critically analyse and interpret the results of analysis pipelines.
- Communicate effectively with peers, professionals and stakeholders with different areas of expertise and interests in biomedicine.
- Explain the ethics and privacy challenges of working with biomedical data, and of methodologies supporting reproduciable biomedical research.
Content
You will learn how to work with genomic data (alignment, mapping, annotation, genome-scale studies). The unit will also cover applied machine learning in the biomedical context (protein structures, gene editing, deep learning for genomics). You will also learn to work with and integrate multi-omics data. The unit will also cover how to use electronic health records or wearables for diagnosis as well as for biomedical research. Finally we will also discuss the ethics and privacy challenges around the use of biomedical data, as well as how to ensure analyses are reproducible.
Learning Approaches
In this unit you will learn through engaging in the following activities:
- Lectures (2 hours), which provide the theoretical basis of the subject.
- Tutorials (1 hour), which provide an opportunity to work in groups on case studies to investigate and develop data science solutions.
- Practical (1 hour), which allow you to apply theory to practical problems using available software tools.
The learning process will be focused on real-world scenarios. Emphasis will be placed on theoretical work, laboratory exercises and case studies. The exercises will be designed to reinforce key concepts and to assist in the completion of the assessments.
Feedback on Learning and Assessment
You can obtain feedback on your progress throughout the unit through asking the teaching staff for advice
and assistance during lectures and practical sessions. You will also receive peer feedback on several assessment items throughout the semester.
The assessments will be marked according to a criteria sheet and returned to you with written feedback within two weeks of submission.
Assessment
Overview
The assessments in this unit are designed for you to demonstrate a critical understanding of biomedical data science, as well as an implementation of data science solutions with the practical skills acquired during the tutorials. The project will allow you to demonstrate your understanding of the methods and challenges associated with biomedical data science. You will also demonstrate your critical skills by providing feedback to your peers, and will benefit from their formative assessment of your work.
Assessment criteria will be made available at the introduction of each assignment.
Unit Grading Scheme
7- point scale
Assessment Tasks
Assessment: Portfolio
You will gradually build a portfolio of work throughout the semester, to show the development of your knowledge, understanding and capabilities across a range of biomedical data types and problems. As part of this assessment, you will be required to write a brief reflection to discuss your development across the semester, with a focus on ethics and on scientific reproducibility.
This assignment is eligible for the 48-hour late submission period and assignment extensions.
Assessment: Project
Practical project applying modern Data Science techniques to an authentic Biomedical question. Includes peer evaluation to critically reflect upon approaches to working collaboratively on a Biomedical project.
This assignment is eligible for the 48-hour late submission period and assignment extensions.
Assessment: Presentation
Short oral presentation summarising your project, its objectives and its conclusions.
Academic Integrity
Academic integrity is a commitment to undertaking academic work and assessment in a manner that is ethical, fair, honest, respectful and accountable.
The Academic Integrity Policy sets out the range of conduct that can be a failure to maintain the standards of academic integrity. This includes, cheating in exams, plagiarism, self-plagiarism, collusion and contract cheating. It also includes providing fraudulent or altered documentation in support of an academic concession application, for example an assignment extension or a deferred exam.
You are encouraged to make use of QUT’s learning support services, resources and tools to assure the academic integrity of your assessment. This includes the use of text matching software that may be available to assist with self-assessing your academic integrity as part of the assessment submission process.
Breaching QUT’s Academic Integrity Policy or engaging in conduct that may defeat or compromise the purpose of assessment can lead to a finding of student misconduct (Code of Conduct – Student) and result in the imposition of penalties under the Management of Student Misconduct Policy, ranging from a grade reduction to exclusion from QUT.
Requirements to Study
Costs
No extraordinary charges or costs are associated with the requirements for this unit.
Resources
A list of open-access resources will be offered to you in week one.
Risk Assessment Statement
There are no extraordinary risks associated with the classroom/lecture activities in this unit.
Course Learning Outcomes
This unit is designed to support your development of the following course/study area learning outcomes.LV41 Bachelor of Biomedical Science
- Critically review, analyse and synthesise foundational knowledge in a broad range of biomedical discipline areas and in depth theoretical, technical and practical knowledge in specialised discipline areas.
Relates to: Portfolio, Project - Demonstrate the technical skills required to solve multi-disciplinary problems in biomedical research, industry and clinical settings and do so in an ethical, safe and responsible manner.
Relates to: Portfolio, Project - Demonstrate the cognitive skills required to find solutions to scientific problems.
Relates to: Portfolio, Project , Presentation - Contribute effectively to biomedical projects, either as an individual or as a member of a team, by demonstrating professional behaviour and participating in continuous learning.
Relates to: Portfolio, Project , Presentation - Apply knowledge and skills to rapidly source, critically analyse and communicate biomedical science information using appropriate technologies.
Relates to: Presentation