Accessibility Skip to Global Navigation Skip to Local Navigation Skip to Content Skip to Search Skip to Site Map Menu

STAT435 Data Analysis for Bioinformatics

Due to COVID-19 restrictions, a selection of on-campus papers will be made available via distance and online learning for eligible students.
Find out which papers are available and how to apply on our COVID-19 website

Topics include an overview of genetics and molecular biology; genetic, genomic, and proteomic technologies; analysis of large data sets; incorporation of biological information into the statistical analysis process.

The analysis of large data sets is becoming increasingly important in many areas. The techniques covered in this paper will be applicable to a wide range of data types, including non-biological data. Exposure to other disciplines (in this case biomedical science) is a must for any applied statistician. Interacting with students from other fields is stimulating and will help you appreciate your statistical skills.

Paper title Data Analysis for Bioinformatics
Paper code STAT435
Subject Statistics
EFTS 0.1667
Points 20 points
Teaching period Semester 1 (On campus)
Domestic Tuition Fees (NZD) $1,154.90
International Tuition Fees (NZD) $4,801.79

^ Top of page

Eligibility
This paper is open to fourth-year students from the Biological and Medical Sciences, Mathematics and Statistics, and Computer Science. As long as you have skills in one of these areas, any remaining gaps will be filled in during the paper. Experience with R will certainly help.

Enrolments for this paper require departmental permission. View more information about departmental permission.
Contact
mparry@maths.otago.ac.nz
Teaching staff

Associate Professor Mik Black (Department of Biochemistry)

Paper Structure
Main topics:
  • Overview of genetics and molecular biology
  • Introduction to genomics technologies
  • Methods for the statistical analysis of large data sets
  • Application of standard statistical methods
  • Introduction to new purpose-built methods
  • Incorporation of biological information into the statistical analysis process
Teaching Arrangements
One 2-hour session per week.
Textbooks
Textbooks are not required for this paper.
Graduate Attributes Emphasised
Communication, Critical thinking.
View more information about Otago's graduate attributes.
Learning Outcomes
Students who successfully complete the paper will demonstrate in-depth understanding of the central concepts and theories.

^ Top of page

Timetable

Semester 1

Location
Dunedin
Teaching method
This paper is taught On Campus
Learning management system
Other

Topics include an overview of genetics and molecular biology; genetic, genomic, and proteomic technologies; analysis of large data sets; incorporation of biological information into the statistical analysis process.

The analysis of large data sets is becoming increasingly important in many areas. The techniques covered in this paper will be applicable to a wide range of data types, including non-biological data. Exposure to other disciplines (in this case biomedical science) is a must for any applied statistician. Interacting with students from other fields is stimulating and will help you appreciate your statistical skills.

Paper title Data Analysis for Bioinformatics
Paper code STAT435
Subject Statistics
EFTS 0.1667
Points 20 points
Teaching period Semester 1 (On campus)
Domestic Tuition Fees Tuition Fees for 2022 have not yet been set
International Tuition Fees Tuition Fees for international students are elsewhere on this website.

^ Top of page

Eligibility
This paper is open to fourth-year students from the Biological and Medical Sciences, Mathematics and Statistics, and Computer Science. As long as you have skills in one of these areas, any remaining gaps will be filled in during the paper. Experience with R will certainly help.

Enrolments for this paper require departmental permission. View more information about departmental permission.
Contact

martin.hazelton@otago.ac.nz    

Teaching staff

Associate Professor Mik Black (Department of Biochemistry)

Paper Structure
Main topics:
  • Overview of genetics and molecular biology
  • Introduction to genomics technologies
  • Methods for the statistical analysis of large data sets
  • Application of standard statistical methods
  • Introduction to new purpose-built methods
  • Incorporation of biological information into the statistical analysis process
Teaching Arrangements
One 2-hour session per week.
Textbooks
Textbooks are not required for this paper.
Graduate Attributes Emphasised
Communication, Critical thinking.
View more information about Otago's graduate attributes.
Learning Outcomes
Students who successfully complete the paper will demonstrate in-depth understanding of the central concepts and theories.

^ Top of page

Timetable

Semester 1

Location
Dunedin
Teaching method
This paper is taught On Campus
Learning management system
Other