BIN315 Selected Topics in Functional Genomics

Credits (ECTS):10

Course responsible:Torgeir Rhodén Hvidsten

Campus / Online:Taught campus Ås

Teaching language:Engelsk

Limits of class size:100

Course frequency:Even years

Nominal workload:

  • Lectures: 20 hours
  • Computer labs: 56 hours
  • Individual study: 174 hours

Teaching and exam period:This course starts in the autumn parallel. This course has teaching/evaluation in the autumn parallel.

About this course

The course will cover bioinformatics methods that are crucial components in all interdisciplinary projects that seek to describe and understand complex molecular biology systems. We will focus on analyzing data from functional genomics including transcriptomics, proteomics, metabolomics and epigenomics. The methods covered in this course are relevant for several of the UN sustainability goals where modern molecular biology is part of the solution, including goals pertaining to food- and bioenergy-production.

There will be weekly lectures/group discussions and supervised computer exercises. The lectures will primarily introduce the students to the theory behind the bioinformatics methods while the labs will show the students how the methods can be used in practice.

BIN315 complements the course BIN310, which covers bioinformatics analysis of biological sequences.

Learning outcome

KNOWLEDGE: On completion of this course, the students will have general knowledge of the different data types generated within functional genomics ("omics"-data: transcriptomics, proteomics, metabolomics and epigenomics) and will be able to explain the theory behind the most common bioinformatics methods for analyzing such data. These methods include finding differentially expressed genes and gene sets, machine learning, clustering and network analysis, and methods for integrating "omics" data and biological knowledge in e.g. ontologies.

SKILLS: On completion of this course, the students will be able to analyze "omics" data using different methods and will also be able to understand and interpret the results produced by these methods. Given a data set and a biological question, the students should be able to asses which methods and tools to use in order to answer the question.

GENERAL COMPETENCE: The students will be able to perform reproducible analysis of data generated within functional genomics and be equipped to modify relevant methods when new datatypes emerge in the future.

  • One lecture/group discussion per week (two hours). Two supervised computer labs per week (four hours). Weekly hand-ins and a semester project.
  • Active use of Canvas.
  • Introduction to bioinformatics equivalent to BIN210. Statistics equivalent to STAT100.
  • Portfolio assessment including weekly assignments and a semester project. Everything must be passed.


    Portfolio Grading: Passed / Not Passed
  • An external examiner approves the evaluation arrangements for the course.
  • Students must use their own laptop for computer-labs and the project.
  • 1 lecture per week (two hours).

    2 supervised computer lab per week (four hours).

  • Special Requirements in Science