Course syllabus


TDA507 / DIT743 Computational methods in bioinformatics lp2 HT22 (7.5 hp)

Course is offered by the department of Computer Science and Engineering

Contact details

  • Graham Kemp (Examiner),
  • Christopher Kolloff (Teaching Assistant),
  • Daniel BrunnsÃ¥ker (Teaching Assistant),
  • Per-Georg Nyholm (Guest Lecturer, Biognos AB)

Course purpose

This course demonstrates how computational methods that have possibly been presented in other computing courses can be applied to solve problems in an application area.
We look at problems related to the analysis of biological sequence data (sequence bioinformatics) and macromolecular structures (structural bioinformatics). Computing scientists need to be able to understand problems that originate in areas that may be unfamiliar to them, and to identify computational methods and approaches that can be used to solve them. Biological concepts needed to understand the problems will be introduced.
This is an advanced level course which uses research articles as the main reference materials. Reading research articles is valuable training for scientists and researchers.
These demonstrate how to present ideas and methods, and how to critically evaluate them. Developing skill in reading research articles is useful preparation for future scientific investigations, and one's own scientific writing can improve through reading.

Computational methods and concepts featured in this course include: dynamic programming; heuristic algorithms; graph partitioning; image skeletonisation, smoothing and edge detection; clustering; sub-matrix matching; geometric hashing; constraint logic programming; Monte Carlo optimisation; simulated annealing; self-avoiding walks.
Biological problems featured in this course include: sequence alignment; domain assignment; structure comparison; comparative modelling; protein folding; fold recognition; finding channels; molecular docking; protein design.



Course literature

Lecture slides; web-based resources; selected research articles

Course design

The preliminary schedule for the course is as follows:

Preliminary schedule
Date Topic
Tue 2022-11-01 Introduction
Wed 2022-11-02 Sequence alignment
Tue 2022-11-08 Protein conformation; protein domains
Wed 2022-11-09 Macromolecular structure determination by X-ray crystallography
Tue 2022-11-15 Macromolecular structure determination by NMR
Wed 2022-11-16 Molecular mechanics; Monte Carlo algorithms; comparative modelling; side chain modelling
Tue 2022-11-22 Fold recognition; de novo protein modelling; lattice models
Wed 2022-11-23 Protein design
Tue 2022-11-29 Markov state models
Wed 2022-11-30 Molecular dynamics
Tue 2022-12-06 Surface representation; docking
Wed 2022-12-07 Channels; Multi-resolution modelling
Tue 2022-12-13 Computational drug design (Guest lecture: Per-Georg Nyholm, Biognos)
Wed 2022-12-14

Topical topics: AlphaFold, COVID-19; Summary

Lecture slides, supplementary material and assignment task descriptions will be made available through the Canvas system. Canvas will also be used for assignment submissions.

Research articles will be listed on these web pages during the course. All of them should be accessible from within the Chalmers (and probably also GU) network. If you are not on campus, you can use VPN (Virtual Private Network) . If you have difficulty accessing any of the materials, please let me know.

Later in this course you will find it useful to look at protein structures with molecular visualisation software. You might want to take a look at UCSF Chimera, RasMol, Jmol or PyMOL. UCSF Chimera and RasMol are installed on the Chalmers Linux system.

Changes made since the last occasion

There are no major changes since the last occasion.

Learning objectives and syllabus

Learning objectives:

Knowledge and understanding

  • describe and summarise problems that have been addressed in the bioinformatics literature, and computational approaches to solving them

Competence and skills

  • design and implement computational solutions to problems in bioinformatics

Judgement and approach

  • critically discuss different bioinformatics methods that address the same task or related tasks, and to discuss differences in the tasks addressed, or differences in the computational approaches
  • identify situations where the same computational methods are applied in addressing different problems, even across different application areas


Link to the syllabus: Chalmers.

Link to the syllabus: GU.

Examination form

The course is examined by individual programming assignments and written assignments.

Academic integrity and honesty

Make sure that you know the rules for how to cite and reference sources that is used in your assignment reports, and how academic dishonesty is treated by Chalmers.

Academic integrity and honesty

If you have any questions or doubts about what is acceptable, please discuss this with the examiner.

Course summary:

Date Details Due