Computational Immunology

Course content

Computational biology and analyses are part of most basic and clinical immunology and inflammation research activities, facilitating the interpretation and integration of large and diverse data sets to gain new insights into the cellular and molecular mechanisms of immune response and disease.

Through this course, students will gain practical experience with methods of computational immunology. In weekly practical exercises, students will analyze, visualize, and interpret data related to topics of immunology and inflammation.

Lectures leading up to each exercise will provide students with a basic understanding of the principles underlying computational methods used in immunological research. The lectures will incorporate examples of use in current research from both academic and industry settings, providing students with insights to real-world applications of these methods.

The course includes analysis of bulk and single cell RNA seq and epigenetic seq data, cytometry data analysis, integration of multi-omics data and network analyses, data visualization, B/T cell receptor analysis, protein structure and interaction prediction.

The methods and tools learned will be integrated in study exercises and coursework of other course of the MSc program.

Education

Msc in Immunology and Inflammation

Learning outcome

After completing the course the student is expected to be able to:

Knowledge

  • Locate publicly available bioinformatics databases
  • Locate publicly available computational biology tools and software resources
  • Understand the basic principles of key bioinformatics methods

 

Skills

  • Identify appropriate computational tools and methods for the analysis of Omics and network data
  • Identify appropriate computational tools and methods for analysis and prediction of protein folding and interactions
  • Utilize publicly available bioinformatics databases
  • Manipulate, analyze, visualize and present data relating to immunological research
  • Interpret and extract meaningful insights from large-scale immunological datasets, network models of the immune system and models of molecular interactions.

 

Competence

  • Understand and evaluate computational biology papers published in peer-reviewed immunological journals
  • Critically analyze and discuss experimental data in the field of computational immunology
  • Conceptually develop and initiate small computational analyses within the field of immunology

Practical exercise course including lectures, journal club, student oral presentation of data analyses.

  • Selected introduction papers to bioinformatics methods
  • Selected scientific papers
  • Experimental course material

 

Continuous feedback during the course of the semester
ECTS
7,5 ECTS
Type of assessment
Oral exam on basis of previous submission, 20 minutes, under invigilation
Type of assessment details
The exam consists of a group-project report including extraction, analysis, and interpretation of biological data sets, as well as an individual oral examination of the analyses performed.
Exam registration requirements

None

Aid
All aids allowed
Marking scale
passed/not passed
Censorship form
No external censorship
Internal examiners
Criteria for exam assessment

To pass, the student must be able to, at an acceptable level:

Knowledge

  • Demonstrate knowledge of strengths and limitations of diverse computational biology methods for the interpretation of disease and biology. 

  • Demonstrate knowledge of databases and tools for computational biology.

 

Skills

  • Search, extract, analyse and visualize data from publicly available databases

  • Apply computational biology software for analysis of Omics, network and protein structure analyses

  • Visualize, present data and conclusions drawn from analysis of immunological research data.

  • Category
  • Hours
  • Lectures
  • 7
  • Preparation
  • 132,5
  • Exercises
  • 21
  • Project work
  • 35
  • Exam Preparation
  • 10
  • Exam
  • 0,5
  • English
  • 206,0

Kursusinformation

Language
English
Course number
SIIK24002U
ECTS
7,5 ECTS
Programme level
Full Degree Master
Duration

1 block

Placement
Block 1
Schedulegroup
---
Capacity
30
Studyboard
Study Board for Human Biology, Immunology and Neuroscience
Contracting department
  • Department of Immunology and Microbiology
Contracting faculty
  • Faculty of Health and Medical Sciences
Course Coordinators
  • Thomas Lavstsen   (7-766a716f63756e4275777066306d7730666d)
  • Farideh Moharrek   (16-6863746b66676a306f716a637474676d4275777066306d7730666d)
Teacher

Professors and associate Professors from Department of Immunology and Microbiology, University of Copenhagen, Technical University of Denmark (DTU) and industry and industry researchers.

Saved on the 03-04-2024

Are you BA- or KA-student?

Are you bachelor- or kandidat-student, then find the course in the course catalog for students:

Courseinformation of students