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55662-01 - Lecture: Applied Mathematics and Informatics in Drug Discovery 2 CP

Semester fall semester 2023
Course frequency Every fall sem.
Lecturers Jitao David Zhang (jitao-david.zhang@unibas.ch, Assessor)
Content Applied mathematics and computer science are indispensable in modern drug discovery to enable decisions that have direct impacts on lives. This introductory course will offer a practitioner’s review of mathematical concepts, informatics tools, and industrial approaches in relevant fields, especially bioinformatics, molecular modelling, cheminformatics, mathematical modelling, experiment design and statistical inference, and machine learning. It is hoped that the students are exposed to the interdisciplinary and multiscale modelling nature of drug discovery, and are motivated to deepen their knowledge in relevant fields in future study and practice, to be able to solve open challenges in drug discovery.
Learning objectives We explore the drug-discovery process and study applications of mathematics and informatics with case studies. We examine how mathematics concepts and informatics tools are used to model complex systems at multiple levels - molecular level, cellular and omics level, organ- and system-level, and population level - and how the multiscale modelling approach contributes to drug discovery.
Bibliography Lecture notes and slides. Recommend reading (papers, book chapters, etc.) and media (e.g. YouTube videos) will be distributed.
Weblink Check out the website at www.amidd.ch

 

Admission requirements Students of natrual sciences, including biology, physics, chemistry, pharmacy, and medical students are as much welcome as students of mathematics and computer sciences.

Though no prerequisite courses are obligatory, elementary understanding of statistics, probability, calculus, and ordinary differential equations are helpful. High-school knowledge in physics, chemistry, and biology are required. Knowledge and proficiency in at least one programming language (preferably C/C++, Java, R, Python, or Julia) is very helpful to try real-world problems.
Language of instruction English
Use of digital media No specific media used
Course auditors welcome

 

Interval Weekday Time Room
wöchentlich Friday 12.15-14.00 Spiegelgasse 5, Seminarraum 05.002

Dates

Date Time Room
Friday 22.09.2023 12.15-14.00 Spiegelgasse 5, Seminarraum 05.002
Friday 29.09.2023 12.15-14.00 Spiegelgasse 5, Seminarraum 05.002
Friday 06.10.2023 12.15-14.00 Spiegelgasse 5, Seminarraum 05.002
Friday 13.10.2023 12.15-14.00 Spiegelgasse 5, Seminarraum 05.002
Friday 20.10.2023 12.15-14.00 Spiegelgasse 5, Seminarraum 05.002
Friday 27.10.2023 12.15-14.00 Spiegelgasse 5, Seminarraum 05.002
Friday 03.11.2023 12.15-14.00 Spiegelgasse 5, Seminarraum 05.002
Friday 10.11.2023 12.15-14.00 Spiegelgasse 5, Seminarraum 05.002
Friday 17.11.2023 12.15-14.00 Bernoullistrasse 30/32, kleiner Hörsaal 120
Friday 24.11.2023 12.15-14.00 Dies Academicus
Friday 01.12.2023 12.15-14.00 Spiegelgasse 5, Seminarraum 05.002
Friday 08.12.2023 12.15-14.00 Spiegelgasse 5, Seminarraum 05.002
Friday 15.12.2023 12.15-14.00 Spiegelgasse 5, Seminarraum 05.002
Friday 22.12.2023 12.15-14.00 Spiegelgasse 5, Seminarraum 05.002
Modules Modul: Applications and Related Topics (Bachelor's degree subject: Computer Science)
Module: Applications and Related Topics (Bachelor's Studies: Computer Science)
Module: Applied Mathematics (Bachelor's Studies: Mathematics)
Module: Electives in Data Science (Master's Studies: Data Science)
Assessment format continuous assessment
Assessment details Scores will be given in scale 1-6 by 0.5. The final note is given by participation including quizzes (30%), offline activities (40%), and a collaboration challenge in the final session (30%).
Assessment registration/deregistration Reg.: course registration, dereg: cancel course registration
Repeat examination no repeat examination
Scale 1-6 0,5
Repeated registration as often as necessary
Responsible faculty Faculty of Science, studiendekanat-philnat@unibas.ch
Offered by Fachbereich Mathematik

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