IFN646 Biomedical Data Science


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Unit Outline: Semester 2 2024, Gardens Point, Internal

Unit code:IFN646
Credit points:12
Pre-requisite:(IFN509 OR IFQ509 and enrolment in IN20 or IN27 ) or (IFN509 or IFQ509 and enrolment in IV53 or IV55 or IV56) or (192cps in IV04 or enrolment in IV54).
Coordinator:Dimitri Perrin | dimitri.perrin@qut.edu.au
Disclaimer - Offer of some units is subject to viability, and information in these Unit Outlines is subject to change prior to commencement of the teaching period.

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:

  1. Discuss biomedical technologies and their suitability for specific applications.
  2. Analyse complex biomedical data using appropriate methodologies and tools, and implement data analysis pipelines
  3. Critically analyse and interpret the results of analysis pipelines.
  4. Communicate effectively with peers, professionals and stakeholders with different areas of expertise and interests in biomedicine.
  5. 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

A series of tasks relating to the content presented in lectures and tutorials.

This assignment is eligible for the 48-hour late submission period and assignment extensions.

Weight: 30
Individual/Group: Individual
Due (indicative): Throughout semester
Related Unit learning outcomes: 1, 2, 3, 5

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.

Weight: 55
Individual/Group: Individual and group
Due (indicative): End of Semester
Related Unit learning outcomes: 1, 2, 3, 4, 5

Assessment: Presentation

Short oral presentation summarising your project, its objectives and its conclusions.

Weight: 15
Individual/Group: Individual and group
Due (indicative): End of Semester
Related Unit learning outcomes: 3, 4

Academic Integrity

Students are expected to engage in learning and assessment at QUT with honesty, transparency and fairness. Maintaining academic integrity means upholding these principles and demonstrating valuable professional capabilities based on ethical foundations.

Failure to maintain academic integrity can take many forms. It includes cheating in examinations, plagiarism, self-plagiarism, collusion, and submitting an assessment item completed by another person (e.g. contract cheating). It can also include providing your assessment to another entity, such as to a person or website.

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.

Further details of QUT’s approach to academic integrity are outlined in the Academic integrity policy and the Student Code of Conduct. Breaching QUT’s Academic integrity policy is regarded as student misconduct and can lead to the imposition of penalties 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

  1. 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
  2. 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
  3. Demonstrate the cognitive skills required to find solutions to scientific problems.
    Relates to: Portfolio, Project , Presentation
  4. 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
  5. Apply knowledge and skills to rapidly source, critically analyse and communicate biomedical science information using appropriate technologies.
    Relates to: Presentation