UiB Blogg            

Bioinformatics for functional metagenomics (BIN420)

Dates: 4-8 September 2017

Location: NMBU Ås

Organiser: Phillip B. Pope

Lecturers: Torgeir Hvidsten, Knut Rudi, Magnus Arntzen, Paulo Jorge de Almeida Borges, Torstein Tengs, J. Chris Gaby (NMBU)

Invited lecturer: Johannes Dröge (Chalmers University of Technology and University of Gothenburg 

Credits: 5 ECTS.

Evaluation: Report based, pass/fail

Registration: Here by 7 August


Course content:

Microbial communities are renowned for the influences they exert in nature as well as industrial applications. They encompass an extraordinary level of species complexity that is invaluable to the overall function of the community. However, our understanding is severely restricted due to the inherent species complexity and the fact that the majority of microbes that exist in nature cannot be cultivated.

This course will introduce, explore and assess the vast array of sequencing technology and bioinformatic methods that are available to address these core issues. The course will include an array of contrasting tools to decrypt microbial communities, including those that assess community structure (metagenomics, predictive genome-reconstruction) and function (metatranscriptomics, metaproteomics).


Learning outcomes:

  • Ability to design experiments and select appropriate methods and/or software
  • Explain the microbial population structure within a microbial community
  • Ability to perform and assess assembly and taxonomic binning methods as well as interpret output quality
  • Ability to combine the output from different omics methods to interpret the predicted function of uncultured microorganisms within a microbial community
  • Explain the shortcomings about these types of analyses


Learning activities:

Intensive one week course and one project assignment with written report. Each course day will consist of:

  • two one-hour lectures
  • supervised computer lab (five hours).



Familiarity with Linux and a programming language (preferably Python and/or R) is expected. Basic knowledge in microbiology is also required.