Multivariate Data Analysis & Machine Learning in Biology (QBIO7002)

Course overview

Biological datasets often include large numbers of features (e.g., species, climatic variables, morphological attributes) that exhibit complex, nonlinear relationships with each other. The human brain, unassisted, is ill-equipped to deal with such information-rich datasets. When the number of features is especially large, or the relationships between them especially complex, even generalized linear models (QBIO7005), the tool-of-choice in scientific inference, may not be up to the job. In this course students will learn the essential theory behind the most commonly used unsupervised and supervised learning techniques in ecological and evolutionary research, and implement these techniques using R to find solutions to a range of real world biological problems. The first half of the course will focus on supervised learning (weeks 1-5), with an emphasis on classification and regression problems. The second half of the course (weeks 6-10) will focus on multivariate data and unsupervised learning, with an emphasis on clustering and dimension reduction. 

Classical multivariate data analysis and modern machine learning algorithms provide a powerful solution to the joint problem of complexity and nonlinearity. A strength of several multivariate techniques (aka unsupervised learning algorithms) is the reduction of high-dimensional variable space into 2-3 tractable dimensions (e.g PCA, PCoA and NMDS); and the natural grouping of observations (e.g. sites or samples) based on their shared properties over numerous features (e.g. hierarchical clustering, k-means clustering). In contrast, many of the most popular supervised machine learning algorithms (e.g. support vector machines, random forests and neural networks) come into their own when a high premium is placed on prediction (e.g. in clinical diagnostics). But there is a cost. What many multivariate techniques and machine learning algorithms make up for in tractability and predictive accuracy, they sacrifice in interpretability. In QBIO7002, students will gain a deep understanding of this trade-off, and the pros and cons of basic methods such as linear regression (low accuracy, high interpretability) versus cutting-edge methods such as neural networks (high accuracy, low interpretability).

Course requirements

Recommended prerequisites

We recommend completing the following courses before enrolling in this one:

Prior knowledge of R or another programming knowledge is highly recommended

Jointly taught details

This course is jointly-taught with:

• Another instance of the same course

All material and workshop shared across QBIO7002 Internal and External.

Course contact

Course staff

Timetable

The timetable for this course is available on the UQ Public Timetable.

Aims and outcomes

The aim of QBIO7002 is to provide students with a solid foundation in the essential theory behind the most commonly used unsupervised and supervised learning techniques in biology, and to equip students with the core skills to implement these techniques to find solutions to a range of real world biological problems.

Learning outcomes

After successfully completing this course you should be able to:

Assessment

Assessment summary

Assessment details

Engagement with Pre-class Reading (Supervised Learning Module)

Mode

Activity/ Performance, Written

Category

Participation/ Student contribution

Weight

10%

Due date

Task 1: 28/02/2025 2:00 pm

Task 2: 14/03/2025 2:00 pm

Task 3: 21/03/2025 2:00 pm

Task 4: 28/03/2025 2:00 pm

Other conditions

Student specific.

See the conditions definitions

Task description

Submission guidelines

Online submission by Turnitin only by the due date. No hard copy or assignment cover sheets required.

Deferral or extension

You may be able to apply for an extension.

The maximum extension allowed is 28 days. Extensions are given in multiples of 24 hours.

See the Additional assessment information section further below for information relating to extension and deferral applications.

Late submission

A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.

You are required to submit assessable items on time. If you fail to meet the submission deadline for any assessment item, then 10% of the maximum possible mark for the assessment item (assessment ‘marked from’ value) will be deducted as a late penalty for every day (or part day) late after the due date. For example, if you submit your assignment 1 hour late, you will be penalised 10%; if your assignment is 24.5 hours late, you will be penalised 20% (because it is late by one 24-hour period plus part of another 24-hour period).

Supervised Learning Assignment

Mode

Written

Category

Computer Code, Paper/ Report/ Annotation

Weight

40%

Due date

15/04/2025 2:00 pm

Other conditions

Student specific.

See the conditions definitions

Task description

Submission guidelines

Online submission by Turnitin only by the due date. No hard copy or assignment cover sheets required.

Deferral or extension

You may be able to apply for an extension.

The maximum extension allowed is 28 days. Extensions are given in multiples of 24 hours.

See the Additional assessment information section further below for information relating to extension and deferral applications.

Late submission

A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.

You are required to submit assessable items on time. If you fail to meet the submission deadline for any assessment item, then 10% of the maximum possible mark for the assessment item (assessment ‘marked from’ value) will be deducted as a late penalty for every day (or part day) late after the due date. For example, if you submit your assignment 1 hour late, you will be penalised 10%; if your assignment is 24.5 hours late, you will be penalised 20% (because it is late by one 24-hour period plus part of another 24-hour period).

Engagement with Pre-class Reading (Unsupervised Learning Module)

Mode

Activity/ Performance, Written

Category

Participation/ Student contribution

Weight

10%

Due date

Task 5: 4/04/2025 2:00 pm

Task 6: 11/04/2025 2:00 pm

Task 7: 17/04/2025 2:00 pm

Task 8: 9/05/2025 2:00 pm

Task 9: 16/05/2025 2:00 pm

Other conditions

Student specific.

See the conditions definitions

Task description

Submission guidelines

Online submission by Turnitin only by the due date. No hard copy or assignment cover sheets required.

Deferral or extension

You may be able to apply for an extension.

The maximum extension allowed is 28 days. Extensions are given in multiples of 24 hours.

See the Additional assessment information section further below for information relating to extension and deferral applications.

Late submission

A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.

You are required to submit assessable items on time. If you fail to meet the submission deadline for any assessment item, then 10% of the maximum possible mark for the assessment item (assessment ‘marked from’ value) will be deducted as a late penalty for every day (or part day) late after the due date. For example, if you submit your assignment 1 hour late, you will be penalised 10%; if your assignment is 24.5 hours late, you will be penalised 20% (because it is late by one 24-hour period plus part of another 24-hour period).

Unsupervised Learning Assignment

Mode

Written

Category

Paper/ Report/ Annotation

Weight

40%

Due date

27/05/2025 2:00 pm

Task description

Submission guidelines

Online submission by Turnitin only by the due date. No hard copy or assignment cover sheets required.

Deferral or extension

You may be able to apply for an extension.

The maximum extension allowed is 28 days. Extensions are given in multiples of 24 hours.

See the Additional assessment information section further below for information relating to extension and deferral applications.

Late submission

A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.

You are required to submit assessable items on time. If you fail to meet the submission deadline for any assessment item, then 10% of the maximum possible mark for the assessment item (assessment ‘marked from’ value) will be deducted as a late penalty for every day (or part day) late after the due date. For example, if you submit your assignment 1 hour late, you will be penalised 10%; if your assignment is 24.5 hours late, you will be penalised 20% (because it is late by one 24-hour period plus part of another 24-hour period).

Course grading

Full criteria for each grade is available in the Assessment Procedure.

Supplementary assessment

Supplementary assessment is available for this course.

Additional assessment information

Assessment Submission

It is the responsibility of the student to ensure the on time, correct and complete submission of all assessment items.

Please ensure you receive and save the submission confirmation for all submitted items, you may be asked to produce this as evidence of your submission.

Applications for Extensions to Assessment Due Dates

Extension requests are submitted online via my.UQ – applying for an extension. Extension requests received in any other way will not be approved. Additional details associated with extension requests, including acceptable and unacceptable reasons, may be found at my.UQ.

Please note:

• Requests for an extension to an assessment due date must be submitted through your my.UQ portal and you must provide documentation of your circumstances, as soon as it becomes evident that an extension is needed. Your application must be submitted on or before the assessment item's due date and time.
• Applications for extension can take time to be processed so you should continue to work on your assessment item while awaiting a decision. We recommend that you submit any completed work by the due date, and this will be marked if your application is not approved. Should your application be approved, then you will be able to resubmit by the agreed revised due date.
• If an extension is approved, you will be notified via your my.UQ portal and the new date and time for submission provided. It is important that you check the revised date as it may differ from the date that you requested.
• If the basis of the application is a medical condition, applications should be accompanied by a medical certificate dated prior to the assignment due date. If you are unable to provide documentation to support your application by the due date and time you must still submit your application on time and attach a written statement (Word document) outlining why you cannot provide the documentation. You must then upload the documentation to the portal within 24 hours.
• If an extension is being sought on the basis of exceptional circumstances, it must be accompanied by supporting documentation (eg. Statutory declaration).
• For extensions based on a SAP you may be granted a maximum of 7 days (if no earlier maximum timeframe applies). See the Extension or Deferral availability section of each assessment for timeframes. Your SAP is all that is required as documentation to support your application. However, additional extension requests for the assessment item will require the submission of additional supporting documentation e.g., a medical certificate. All extension requests must be received by the assessment due date and time.
• An extension for an assessment item due within the teaching period in which the course is offered, must not exceed four weeks in total. If you are incapacitated for a period exceeding four weeks of the teaching period, you are advised to apply for Removal of Course.
• If you have been ill or unable to attend class for more than 4 weeks, you are advised to carefully consider whether you are capable of successfully completing your courses this semester. You might be eligible to withdraw without academic penalty - seek advice from the Faculty that administers your program.
• Students may be asked to submit evidence of work completed to date. Lack of adequate progress on your assessment item may result in an extension being denied.
• There are no provisions for exemption from an assessment item within UQ rules. If you are unable to submit an assessment piece then, under special circumstances, you may be granted an exemption, but may be required to submit alternative assessment to ensure all learning outcomes are met.

Turnitin

All written assessment must be submitted via the appropriate Turnitin submission portal, which can be found within the Blackboard site. You are responsible for ensuring that your submission is complete. It is wise to re-enter the Turnitin portal and confirm that your submission is there and that it has not been altered during the submission process.

By submitting work through Turnitin you are deemed to have accepted the following declaration “I certify that this assignment is my own work and has not been submitted, either previously or concurrently, in whole or in part, to this University or any other educational institution, for marking or assessment”.

In the case of a Blackboard outage, please contact the Course Coordinator as soon as possible to confirm the outage with ITS.

Assessment/Attendance

Please notify your Course Coordinator as soon as you become aware of any issue that may affect your ability to meet the assessment/attendance requirements of the course. The my.UQ website and the Course Profile for your course also provide information about your course requirements, the rules associated with your courses and services offered by the University.

A note for repeating students in this course

Any student who enrols in a course must not be given exemption or partial credit from their previous attempt(s) for any individual piece of assessment. Instead, the student must successfully complete all of the learning activities and assessment items within the study period of enrolment (PPL Assessment - Procedures).

If the same assessment item is set from one year to the next, repeating students are allowed to submit the same work they submitted in previous attempts at the course. Where possible SENV recommends that you use the feedback you received in your last attempt to improve parts of the item where you lost marks. Resubmission of an altered or unaltered assessment item by a repeating student (where the same assessment has been set) will not be considered as self-plagiarism.

Plagiarism

You should be aware that the University employs purpose built software to detect plagiarism. It is very important that you understand clearly the practical meaning of plagiarism.

DEFINITION OF PLAGIARISM: Plagiarism is the act of misrepresenting as one's own original work the ideas, interpretations, words or creative works of another. These include published and unpublished documents, designs, music, sounds, images, photographs, computer codes and ideas gained through working in a group. These ideas, interpretations, words or works may be found in print and/or electronic media.

EXAMPLES OF PLAGIARISM:

1. Direct copying of paragraphs, sentences, a single sentence or significant parts of a sentence;

2. Direct copying of paragraphs, sentences, a single sentence or significant parts of a sentence with an end reference but without quotation marks around the copied text;

3. Copying ideas, concepts, research results, computer codes, statistical tables, designs, images, sounds or text or any combination of these;

4. Paraphrasing, summarising or simply rearranging another person's words, ideas, etc without changing the basic structure and/or meaning of the text;

5. Offering an idea or interpretation that is not one's own without identifying whose idea or interpretation it is;

6. A 'cut and paste' of statements from multiple sources;

7. Presenting as independent, work done in collaboration with others;

8. Copying or adapting another student's original work into a submitted assessment item.

Learning resources

You'll need the following resources to successfully complete the course. We've indicated below if you need a personal copy of the reading materials or your own item.

Library resources

Library resources are available on the UQ Library website.

Learning activities

The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.

Policies and procedures

University policies and procedures apply to all aspects of student life. As a UQ student, you must comply with University-wide and program-specific requirements, including the:

• Student Code of Conduct Policy
• Student Integrity and Misconduct Policy and Procedure
• Assessment Procedure
• Examinations Procedure
• Reasonable Adjustments - Students Policy and Procedure

Learn more about UQ policies on my.UQ and the Policy and Procedure Library.