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Welcome to the website for Applied Mathematics and Informatics In Drug Discovery (AMIDD), the course series running at the Department of Mathematics and Informatics, University of Basel in the fall semester 2021.

The course series introduces interdisciplinary research in drug discovery with mathematics as the language and informatics as the tool. We have a diverse and lively class room that learn together and from each other: every year about two third students of the class study mathematics or computer science, while other students study physics, chemistry, (computational) biology, pharmacy, and other fields such as epidemiology and medicine.

More information on the course can be found at the course directory of the University Basel.

Table of content

Lectures with Zoom

Due to the coronavirus pandemic, the course in 2021 will take place online with Zoom exclusively. The link to join the Zoom meeting is: https://unibas.zoom.us/j/68803401669. The passcode for the Zoom meeting is shared among registered students via emails.

Time and place

The lecture takes place on Fridays between 12:15 and 14:00 on Zoom. The meeting will be active between 12:00 and 14:00, so that any questions can be addressed before the lecture.

Course material and licensing

Course material, including lecture notes, slides, and reading material, are shared on the course’s web site, AMIDD.ch, unless otherwise specified in the course.

All Zoom sessions are recorded and distributed among attendees.

All course material, unless otherwise stated, is shared under the Creative Commons (CC-BY-SA 4.0) license.

Pre-course survey

Prior to attending the first session, please fill out the voluntary pre-course survey. It helps me to shape the course to meet your needs.

Syllabus

1. Drug discovery: an overview

2. The central dogma and drug discovery

3. Biological sequence analysis

4. From sequences to structures

5. Proteins and ligands

6. Structure- and ligand-based drug design

7. Omics and cellular modelling

8. PK/PD and PBPK modelling

9. Population modelling and clinical trials

10. Dies academicus - optional Ask Me Anything session

You can ask me anything in this session, which will be exceptionally not recorded.

Besides scientific topics in drug discovery, my experience is that many students are interested in career topics: should I do a PhD or not? Should I consider working in industry? These and other questions are asked again and again. While I cannot provide any definitive answer for you, I am glad to share some of my thoughts. For instance, you may this article below interesting if you consider doing a PhD and perhaps doing a postdoc in pharma: Zhang, Jitao David. “Ten Simple Rules for Doing a Postdoc in Pharma.” PLOS Computational Biology 17, no. 6 (June 3, 2021): e1008989.

11. Guest-speaker session

12. Student presentation (I)

13. Student presentation (II)

Student presentation topics and reference papers

You can vote for your presentation topics via Google Form by November the first.

End-term project

Assessment

The final note is given by participation (40%), presentation (30%), and project work (30%).

Further questions or suggestions?

Please contact the lecturer, Jitao David Zhang, at jitao-david.zhang@unibas.ch.

Archives of past courses