Course syllabus
This page gives a basic overview of CS369 for Semester 1 2021. All course material is in Modules.
| Course Overview | Digital Course Outline | Staff |
| Class Representatives | Meeting Times | Course Resources |
| Assessments | Course Expectations | Getting Started |
Course Overview
Computational biology is the development and application of computer algorithms and software to address scientific questions in the biological and life sciences. This course includes probabilistic computer modeling, computer-based statistical inference, and computer simulation for, and motivated from, the life sciences. It focuses on modeling and analyzing real-world biological data with an emphasis on analyzing DNA sequence data.
Digital Course Outline
A full overview of the course is provided in the Digital Course Outline
Staff
- Lecturer (weeks 1-3) - Dr Matthew Egbert m.egbert@auckland.ac.nz 303.491
- Lecturer (weeks 4-7) - Dr Katerina Taskova katerina.taskova@auckland.ac.nz Office 303.493
- Lecturer and Course Coordinator (weeks 8-12) - Dr David Welch david.welch@auckland.ac.nz Office 303S.465
- Tutor - Kylie Chen kche309@aucklanduni.ac.nz
Class Representatives
Class reps can act as an intermediary between students in the class and the lecturers and tutors. You can share with them any suggestions/complaints/remarks about the lectures. The class reps are not a part of the teaching team.
- Elected at the start of the semester - let a lecturer know if you are interested
Meeting times
LECTURES take place on
Monday 9am (Clocktower South, Room 039)
Thursday 11am (ConfCentre/423-342)
Friday 11am (OGHLecTh/102-G36)
LABS are scheduled on Mondays and Wednesdays. You attend EITHER
Monday 11 am-12 pm in 303S-B75 OR
Wednesday 11 am-12 pm in 303S-B75 OR
Wednesday 12 pm-1 pm in 303S-B75.
Check SSO for room times
Course Resources and Getting Help
Piazza: Piazza is the main forum we will be using for asking and answering questions. In a large class like this it works well so you are encouraged to participate asking and answering questions there.
Assessments and Pass Requirements
- 30% assignments (4 @ 7.5% each)
- 10% written midterm test
- 60% written final examination
- This course has separate theory and practical pass requirement, i.e., you will need to pass both the theory (test+exam) and the practical (assignments) individually.
- We use the standard university grade boundaries. >89.5 for A+, then 5 mark increments down to >49.5 for C-.
Course Expectations
The document linked below outlines the School of Computer Science's philosophy of learning and teaching and our expectations for student engagement.
Getting Started
The course material is arranged in Modules.
Course summary:
| Date | Details | Due |
|---|---|---|