STAT435 Data Analysis for Bioinformatics

Overview

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.

About this paper

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

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.

Timetable