22145 Immunological Bioinformatics Course Programme Fall 2026: Difference between revisions

Revision as of 16:39, 12 August 2026

General information

Where and when

Classes are held on Wednesdays from 8:00 to 12:00 in Building 208, teaching room 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 coordinator.
Morten Nielsen — Professor and course coordinator.

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 2 consists of a group research project, culminating in a poster presentation on the final day of the course.

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 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 group oral project presentation with individual questions at the end of the course, and a final two-hour written exam. 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.

The written exam questions will be provided as a PDF through the DTU online exam system. PDF is the only accepted submission format.

All aids are permitted during the exam, including books, papers, and notes. You will have open access to the internet, including all materials and websites used during the course. You may also search for information using ChatGPT, Google, Wikipedia, and similar resources. However, you are not permitted to communicate with other people through email, social media, chat services, or file-sharing platforms. Internet traffic may be logged during the exam to ensure compliance with these restrictions.

AI tools are permitted, but you must clearly state where and how you used them in your answers. Please use generative AI carefully: it may produce overly general answers and could cost you valuable exam time.

DTU Learn link

DTU Learn page: https://learn.inside.dtu.dk/d2l/home/271397

Evaluation and feedback

We welcome comments, suggestions, criticism, and praise throughout the semester. You can:

email the teachers; or
post under "General feedback" in the "Discussion" area on DTU Learn.

You may comment on messages posted in the discussion area. When you agree with a comment, please reply with "Agree!" so that the teaching team can see that the feedback is shared by more than one person.

A midterm evaluation will also be conducted shortly after the autumn break through DTU Evaluation.

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

Lectures:

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

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

Exercise: