COMPSCI 369 : Computational Methods in Interdisciplinary Science


2022 Semester One (1223) (15 POINTS)

Course Prescription

Many sciences use computational methods that involve the development and application of computer algorithms and software to answer scientific questions. This course looks at how to tackle these interdisciplinary problems through methods like probabilistic computer modelling, computer-based statistical inference, and computer simulations. The material is largely motivated by the life sciences but also uses examples from other sciences. It focuses on modelling and analysing real-world data with an emphasis on analysing DNA sequence data. No background in physical or life sciences is assumed.

Course Overview

2-3 weeks modeling using dynamical systems and difference equations, 2-3 weeks on sequence alignment and genome assembly algorithms, 2 weeks on introduction to stochastic modelling, 1-2 weeks on hidden Markov models (HMMs) and their applications in sequence analysis, 2-3 weeks on trees and phylogenetics.

Course Requirements

Prerequisite: COMPSCI 220 and 15 points from COMPSCI 225, MATHS 254, 255

Capabilities Developed in this Course

Capability 1: Disciplinary Knowledge and Practice
Capability 2: Critical Thinking
Capability 3: Solution Seeking
Graduate Profile: Bachelor of Science

Learning Outcomes

By the end of this course, students will be able to:
  1. Derive, explain and apply basics of numerical computing (Capability 1, 2 and 3)
  2. Understand and explain how genetic data is collected, processed and stored (Capability 1, 2 and 3)
  3. Understand, explain, and implement basic methods for simulating discrete-time and continuous-time dynamical systems (Capability 1, 2 and 3)
  4. Understand and apply basic probabilistic modelling techniques, including common probability distributions, simple stochastic processes, Markov chains, and hidden Markov models (HMMs) (Capability 1, 2 and 3)
  5. Understand and implement standard dynamic programming algorithms for sequence alignment and hidden Markov models (Capability 1, 2 and 3)
  6. Understand, exaplain and implement methods for simulating from stochastic models (Capability 1, 2 and 3)
  7. Define, explain and apply the maximum likelihood and the least squares framework (Capability 1, 2 and 3)
  8. Understand and explain the basic model of genetic sequence evolution (Capability 1, 2 and 3)
  9. Describe, explain, and analyse phylogenetic models of sequence evolution (Capability 1, 2 and 3)
  10. Score, construct and interpret phylogenetic trees under neighbour joining, parsimony and likelihood based methods (Capability 1, 2 and 3)


Assessment Type Percentage Classification
Assignments 30% Individual Coursework
Test 10% Individual Coursework
Final Exam 60% Individual Examination
Assessment Type Learning Outcome Addressed
1 2 3 4 5 6 7 8 9 10
Final Exam

Special Requirements

To pass the course, students must achieve an overall pass, as well as passes in both the theory component (test and exam) and the practical component (assignments).

Workload Expectations

This course is a standard 15 point course and students are expected to spend 10 hours per week involved in each 15 point course that they are enrolled in.

For this course, you can expect 3 hours of lectures, a 1 hour tutorial during term time. Assignments may take 15-20 hours each. Other time should be spent completing labs, reviewing material, reading outside resources, and studying for the test and exam.

Delivery Mode

Campus Experience

Attendance is expected at scheduled activities.
Lectures will be available as recordings. Other learning activities will not be available as recordings.
The course will not include live online events.
Attendance on campus is required for the test/exam assuming COVID-19 restrictions allow.
The activities for the course are scheduled as a standard weekly timetable.

Learning Resources

Course materials are made available in a learning and collaboration tool called Canvas which also includes reading lists and lecture recordings (where available).

Please remember that the recording of any class on a personal device requires the permission of the instructor.

Course notes and/or slides are provided.
The book Biological Sequence Analysis by Durbin, Eddy, Krogh and Mitchison is recommended (available in the library).

Student Feedback

During the course Class Representatives in each class can take feedback to the staff responsible for the course and staff-student consultative committees.

At the end of the course students will be invited to give feedback on the course and teaching through a tool called SET or Qualtrics. The lecturers and course co-ordinators will consider all feedback.

Your feedback helps to improve the course and its delivery for all students.

Academic Integrity

The University of Auckland will not tolerate cheating, or assisting others to cheat, and views cheating in coursework as a serious academic offence. The work that a student submits for grading must be the student's own work, reflecting their learning. Where work from other sources is used, it must be properly acknowledged and referenced. This requirement also applies to sources on the internet. A student's assessed work may be reviewed against online source material using computerised detection mechanisms.

Class Representatives

Class representatives are students tasked with representing student issues to departments, faculties, and the wider university. If you have a complaint about this course, please contact your class rep who will know how to raise it in the right channels. See your departmental noticeboard for contact details for your class reps.


The content and delivery of content in this course are protected by copyright. Material belonging to others may have been used in this course and copied by and solely for the educational purposes of the University under license.

You may copy the course content for the purposes of private study or research, but you may not upload onto any third party site, make a further copy or sell, alter or further reproduce or distribute any part of the course content to another person.

Inclusive Learning

All students are asked to discuss any impairment related requirements privately, face to face and/or in written form with the course coordinator, lecturer or tutor.

Student Disability Services also provides support for students with a wide range of impairments, both visible and invisible, to succeed and excel at the University. For more information and contact details, please visit the Student Disability Services’ website

Special Circumstances

If your ability to complete assessed coursework is affected by illness or other personal circumstances outside of your control, contact a member of teaching staff as soon as possible before the assessment is due.

If your personal circumstances significantly affect your performance, or preparation, for an exam or eligible written test, refer to the University’s aegrotat or compassionate consideration page

This should be done as soon as possible and no later than seven days after the affected test or exam date.

Learning Continuity

In the event of an unexpected disruption, we undertake to maintain the continuity and standard of teaching and learning in all your courses throughout the year. If there are unexpected disruptions the University has contingency plans to ensure that access to your course continues and course assessment continues to meet the principles of the University’s assessment policy. Some adjustments may need to be made in emergencies. You will be kept fully informed by your course co-ordinator/director, and if disruption occurs you should refer to the university website for information about how to proceed.

The delivery mode may change depending on COVID restrictions. Any changes will be communicated through Canvas.

Student Charter and Responsibilities

The Student Charter assumes and acknowledges that students are active participants in the learning process and that they have responsibilities to the institution and the international community of scholars. The University expects that students will act at all times in a way that demonstrates respect for the rights of other students and staff so that the learning environment is both safe and productive. For further information visit Student Charter


Elements of this outline may be subject to change. The latest information about the course will be available for enrolled students in Canvas.

In this course students may be asked to submit coursework assessments digitally. The University reserves the right to conduct scheduled tests and examinations for this course online or through the use of computers or other electronic devices. Where tests or examinations are conducted online remote invigilation arrangements may be used. In exceptional circumstances changes to elements of this course may be necessary at short notice. Students enrolled in this course will be informed of any such changes and the reasons for them, as soon as possible, through Canvas.

Published on 09/11/2021 10:13 a.m.