Syllabus for Bioinformatic Analyses IIa

Bioinformatiska analyser IIa

A revised version of the syllabus is available.


  • 5 credits
  • Course code: 1BG337
  • Education cycle: Second cycle
  • Main field(s) of study and in-depth level: Biology A1N, Technology A1N
  • Grading system: Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
  • Established: 2007-03-15
  • Established by: The Faculty Board of Science and Technology
  • Revised: 2017-04-19
  • Revised by: The Faculty Board of Science and Technology
  • Applies from: week 27, 2017
  • Entry requirements: Bioinformatic Analyses I.
  • Responsible department: Biology Education Centre

Learning outcomes

The course focuses on evolutionary analyses and analyses of biological diversity. After the course, the student should be able to:

  • explain and justify different models of sequence evolution
  • explain and evaluate different phylogenetic optimality criteria and choose the appropriate criterion to solve a given problem
  • outline and apply the process to carry out and evaluate a phylogenetic analysis and explain its different parts
  • explain the principles of up-to-date multivariate methods
  • choose and apply (for the problem area) existing software on a given biological problem
  • critically analyse, evaluate and compile obtained results


The course mainly deals with bioinformatics with a focus on evolutionary analyses and contains the following parts and aspects:

Models for sequence evolution and statistical sequence comparisons. Phylogenetics; trees and networks, parsimony, distance methods, probability-based methods (maximum likelihood and Bayesian inference). Multivariate methods for reducing dimensionality and visualisation (PCA and MDS). GIS.


The teaching is provided in the form of web-based teaching,computer exercises and project assignment.


Modules: Theory 2 credits; computer exercises 2 credits; project 1 credit
The theory part is examined by a written examination. The modules computer exercises and project are examined in writing.

Reading list

Reading list

Applies from: week 27, 2017

Web-based course material.