BIOL337-21S1 (C) Semester One 2021

Bioinformatics

This occurrence is not offered in 2021

15 points

Details:
Start Date: Monday, 22 February 2021
End Date: Sunday, 27 June 2021
Withdrawal Dates
Last Day to withdraw from this course:
  • Without financial penalty (full fee refund): Sunday, 7 March 2021
  • Without academic penalty (including no fee refund): Friday, 14 May 2021

Description

The general aim of this course is to discuss major concepts in the bioinformatic analysis, application, handling and management of large-scale biological data, and apply these bioinformatics methods to real-world issues. The central focus will be on bringing together previously developed skills in programming, computing and data wrangling, and evaluating how these skills apply to biological datasets. This paper will also discuss the cultural, political, social and legal issues regarding data ownership, use and governance. The course will consist of regular lectures and computer labs, where students will be able to explore biological datasets using their knowledge of bioinformatics. The emphasis is on the amalgamation of students’ previous two years of training and experience, providing students with the context and the background required to apply their skills in the real world. Skills learnt will be assessed via short computer lab reports and a final exam. BIOL337 is a required course for enrolment in BIOL338 (Bioinformatics Project).

Learning Outcomes

Intended Learning Outcomes (Hua Akoranga) and Associated Assessment (Aromatawai)
As a student in this course, I will develop the ability to:
Learning Outcome Number 1
LO1
Demonstrate an understanding of biological data analysis across multiple programming languages, and demonstrate the ability to apply these methods to different types of biological data, to derive biologically meaningful conclusions from the data
(Assessment: written assessments final exam)
Related Graduate Attributes and Kaupapa: Critically competent in the core academic discipline, Biculturally Competent and Confident (kaupapa 1,3,4,5,7), Employable, innovative and enterprising, Globally aware
Learning Outcome Number 2
LO2
Demonstrate an ability to edit and adapt existing bioinformatics analysis methods and pipelines to new datasets
(Assessment: written assessments)
Related Graduate Attributes and Kaupapa: Critically competent in the core academic discipline, Biculturally Competent and Confident (kaupapa 3,4,5,7), Employable, innovative and enterprising, Globally aware
Learning Outcome Number 3
LO3
Show competency in the fitting of appropriate statistical tests to data outputs from LO1
(Assessment: written assessments)
Related Graduate Attributes and Kaupapa: Critically competent in the core academic discipline, Biculturally Competent and Confident (kaupapa 3,4,5,7), Employable, innovative and enterprising
Learning Outcome Number 4
LO4
Demonstrate understanding of the characteristics and limitations of these methods
(Assessment: written assessments final exam)
Related Graduate Attributes and Kaupapa: Critically competent in the core academic discipline, Employable, innovative and enterprising, Globally aware
Learning Outcome Number 5
LO5
Demonstrate an understanding of the importance of biological data ownership and governance, as applied to ethical, social and political issues
(Assessment: written assessments final exam)
 Related Graduate Attributes and Kaupapa: Critically competent in the core academic discipline, Biculturally Competent and Confident (kaupapa 3,4,5,6,7), Employable, innovative and enterprising, Globally aware
Transferable Skills / Pūkenga Ngaio
As a student in this course, I will develop the following skills:
 Synthesising information. In everyday life and in many job situations you will be required to read information from different sources, construct your own understanding and shape your own viewpoint. In lectures and labs we will discuss recent research papers in a group environment and this will develop your abilities to identify the essential elements of research outputs - you will then use in report writing. (Graduate Attribute 2: Employable, Innovative and Enterprising)
 Generating data. Important for research and in governmental and non-governmental organizations. We will conduct research activities to provide both the real-world context for lectures and to develop hands-on skills in data generation, manipulation and interpretation. (Graduate Attribute 2: Employable, Innovative and Enterprising)
 Analysing data. Important for research, as well as in a number of private-sector organizations. This skill will be further developed when you analyse and present the data you generate in the labs. (Graduate Attribute 2: Employable, Innovative and Enterprising)
 Writing a report on findings. Clear written communication is essential for most professional careers. We will provide instruction on the elements of successful reports and help you identify these elements with clear marking rubrics through peer and self-assessment. (Graduate Attribute 2: Employable, Innovative and Enterprising)

Graduate Profile / Āhuatanga Tāura
Critically competent X
Employable, innovative and enterprising X
Biculturally competent and confident X
Engaged with the community
Globally aware X

Prerequisites

Course Coordinator

For further information see School of Biological Sciences Head of Department

Course links

Course Outline

Notes

https://apps.canterbury.ac.nz/1/biology/images/biol337.jpg

Indicative Fees

Domestic fee $910.00

International fee $4,438.00

* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.

For further information see School of Biological Sciences .

All BIOL337 Occurrences

  • BIOL337-21S1 (C) Semester One 2021 - Not Offered