22145 Immunological Bioinformatics Course Programme Fall 2026

General information

Where and when

Classes are held on Wednesdays from 8:00 to 12:00 in Building 208, Holdlokale 3/065, beginning on Wednesday, 2 September 2026, at 09:00.

The first hour of each class 8-9 is dedicated to course preparation, including videos, papers, or other reading material provided on DTU Learn. Unless otherwise specified, we meet at the classroom at 09:00.

Teachers

Carolina Barra Quaglia — Associate Professor and course responsible.
Morten Nielsen — Professor and course responsible.

Teaching assistant

Eric Bautista Farrerons — PhD student.

Course content

The course introduces students to state-of-the-art methods in computational immunology.

The methods are presented in the context of immunology as a domain-specific field. Introductions to the underlying theory are followed by practical exercises, enabling students to perform analyses independently. The course covers immunological bioinformatics and computational vaccinology, with perspectives on infectious diseases, cancer immunotherapy, and autoimmunity.

The course is taught in two parts:

Part 1 consists of lectures and group-based exercises. Part 1 ends with a "in class" written exam on November 11th.
Part 2 consists of a group research project, culminating in a poster presentation on the final day of the course. December 2nd.

Curriculum

There is no required textbook. The curriculum consists of lectures and exercises completed in class, supplemented by papers and book chapters made available on DTU Learn. Please note that all exercise guides are part of the mandatory curriculum, including the answers, which will be made available on DTU Learn after each exercise.

Hand-ins

Regardless of the software used to prepare your work, all submissions must be handed in as PDF files.

Group submissions are permitted and recommended.

The hand-ins are mandatory however, they do not affect your grade. Their main purpose is to help you prepare for the exam and to help the teaching team assess students' understanding. If several participants make the same mistake, the issue will be clarified at the beginning of the following lecture.

Exam

The assessment consists of two parts: a written two-hour written exam in week 10, and a group oral project presentation with individual questions at the end of the course. The final grade is based on an overall assessment of both parts. To pass the course, you must complete the oral presentation and pass the written exam.

All aids are permitted during the written exam, including books, papers, and notes. Internet is not allowed in the written exam You are not permitted to communicate with other people through email, social media, chat services, or any file-sharing platforms. Internet traffic may be logged during the exam to ensure compliance with these restrictions.

The use of generative AI is permitted during the project work, but you must clearly state where and how you used them as stated in DTU guidelines.

Please beware that content, results, links etc. that you discover via generative AI may be incorrect - simply because of the way generative AI models are built.

Generative AI produces content from huge amounts of data collected from the internet. The data that the AI system is based on is not necessarily publicly available and it may be copyright protected.

You are solely responsible to adhere to the academic standards of honesty, transparency and accountability as outlined in DTU's code of honour and Principles for good scientific conduct.

DTU Learn link

DTU Learn page: https://learn.inside.dtu.dk/d2l/home/325135

Lecture and exercise plan

Note: This is a preliminary plan and may be subject to changes. Check the page regularly for updates.

Wednesday, 2 September 2026 — Introduction and databases

Preparation material:

Video: Immunology Recap
Video: Adaptive Immunity
Book chapter: The adaptive Immune system

Lectures: We start at 9am

Introduction to immunological bioinformatics — Carolina Barra Quaglia.
Databases — Carolina Barra Quaglia.

Slides: All slides will be made available on DTU Learn.

Exercise:IEDB