SKBS17005U  Bioinformatics

Volume 2018/2019
Education

BSc in Quantitative Biology and Disease Modeling - compulsory course

Content

Bioinformatics plays a decisive role in molecular biology, but has also become a key topic in medical research. The focus in bioinformatics is on integrative analysis of high-throughput biological data, ranging from molecular-level data on sequences and macromolecular structures to clinical data. A major aim of this is to gain insights into complex diseases such as diabetes and cancer. The objectives of the course are to provide the students knowledge of a range of methods for finding, analyzing and integrating heterogeneous biological data in the context of a specific disease, and to provide them with the necessary foundation to critically evaluate results of such analyses.
Part of the course workload will be in the form of individual/group project work on a specific bioinformatics assignment.

Learning Outcome

After completing the course the student is expected to:

Knowledge

  • Discuss how the information from biological experiments may be represented in an electronic format
  • Discuss how heterogeneous data can be integrated and evaluate

 

Skill

  • Search for data in publicly available databases such as GenBank, PDB 
and STRING
  • Use data analysis programs such as Unix, PyMol and Cytoscape
  • Produce and critically evaluate sequence alignments and protein networks
  • Present heterogeneous data on a biological system for answering biological questions
     

Competence

  • Master a range of methods for finding, analyzing and integrating heterogeneous biological data in the context of a specific disease
  • Critically evaluate results of such analyses
Lectures, excercises, project work.
Written
Oral
Individual
Collective
Continuous feedback during the course of the semester
Credit
5 ECTS
Type of assessment
Oral examination
Oral exam in individual/group project
Exam registration requirements

Course participation + Participation in exercises and subsequent preparation of exercise reports + individual/group project

Aid
All aids allowed
Marking scale
7-point grading scale
Censorship form
No external censorship
More internal examiners.
Criteria for exam assesment

To achieve maximum grade the student must:

Knowledge

  • Discuss how the information from biological experiments may be represented in an electronic format
  • Discuss how heterogeneous data can be integrated and evaluate

 

Skill

  • Search for data in publicly available databases such as GenBank, PDB 
and STRING
  • Use data analysis programs such as Unix, PyMol and Cytoscape
  • Produce and critically evaluate sequence alignments and protein networks
  • Present heterogeneous data on a biological system for answering biological questions
  • Master a range of methods for finding, analyzing and integrating heterogeneous biological data in the context of a specific disease
  • Critically evaluate results of such analyses
  • Category
  • Hours
  • Lectures
  • 35
  • Preparation
  • 70
  • Project work
  • 33
  • Total
  • 138