Course syllabus


TDA507 / DIT743 Computational methods in bioinformatics lp2 HT21 (7.5 hp)

Course is offered by the department of Computer Science and Engineering

Contact details

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:

Mon 2021-11-01 Introduction
Wed 2021-11-03 Sequence alignment
Mon 2021-11-08 Protein conformation; protein domains
Wed 2021-11-10 Macromolecular structure determination by X-ray crystallography
Mon 2021-11-15 Macromolecular structure determination by NMR
Wed 2021-11-17 Molecular mechanics; Monte Carlo algorithms; comparative modelling; side chain modelling
Mon 2021-11-22 Fold recognition; de novo protein modelling; lattice models
Wed 2021-11-24 Protein design
Mon 2021-11-29 Surface representation; docking
Wed 2021-12-01 Channels
Mon 2021-12-06 Multi-resolution modelling (Updated: 2021-12-06)
Pre-recorded Topical topics: AlphaFold; COVID-19 (Updated: 2021-12-06)
Mon 2021-12-13 Summary; guest lecture: Christopher Kolloff (Updated: 2021-12-06)
Wed 2021-12-15

Guest lecture: Per-Georg Nyholm (Biognos), Computational Drug Design (Updated: 2021-12-06)

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 RasMol, UCSF Chimera, Jmol or PyMOL. RasMol and UCSF Chimera 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, written assignments and oral presentations.

Course summary:

Date Details Due