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55662-01 - Vorlesung: Applied Mathematics and Informatics in Drug Discovery (2 KP)
| Semester | Herbstsemester 2023 |
| Angebotsmuster | Jedes Herbstsemester |
| Dozierende | Jitao David Zhang (jitao-david.zhang@unibas.ch, BeurteilerIn) |
| Inhalt | 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. |
| Lernziele | 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. |
| Literatur | 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 |
| Teilnahmevoraussetzungen | 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. |
| Unterrichtssprache | Englisch |
| Einsatz digitaler Medien | kein spezifischer Einsatz |
| HörerInnen willkommen |
| Intervall | Wochentag | Zeit | Raum |
|---|---|---|---|
| wöchentlich | Freitag | 12.15-14.00 | Spiegelgasse 5, Seminarraum 05.002 |
Einzeltermine
| Datum | Zeit | Raum |
|---|---|---|
| Freitag 22.09.2023 | 12.15-14.00 Uhr | Spiegelgasse 5, Seminarraum 05.002 |
| Freitag 29.09.2023 | 12.15-14.00 Uhr | Spiegelgasse 5, Seminarraum 05.002 |
| Freitag 06.10.2023 | 12.15-14.00 Uhr | Spiegelgasse 5, Seminarraum 05.002 |
| Freitag 13.10.2023 | 12.15-14.00 Uhr | Spiegelgasse 5, Seminarraum 05.002 |
| Freitag 20.10.2023 | 12.15-14.00 Uhr | Spiegelgasse 5, Seminarraum 05.002 |
| Freitag 27.10.2023 | 12.15-14.00 Uhr | Spiegelgasse 5, Seminarraum 05.002 |
| Freitag 03.11.2023 | 12.15-14.00 Uhr | Spiegelgasse 5, Seminarraum 05.002 |
| Freitag 10.11.2023 | 12.15-14.00 Uhr | Spiegelgasse 5, Seminarraum 05.002 |
| Freitag 17.11.2023 | 12.15-14.00 Uhr | Bernoullistrasse 30/32, kleiner Hörsaal 120 |
| Freitag 24.11.2023 | 12.15-14.00 Uhr | Dies Academicus |
| Freitag 01.12.2023 | 12.15-14.00 Uhr | Spiegelgasse 5, Seminarraum 05.002 |
| Freitag 08.12.2023 | 12.15-14.00 Uhr | Spiegelgasse 5, Seminarraum 05.002 |
| Freitag 15.12.2023 | 12.15-14.00 Uhr | Spiegelgasse 5, Seminarraum 05.002 |
| Freitag 22.12.2023 | 12.15-14.00 Uhr | Spiegelgasse 5, Seminarraum 05.002 |
| Module |
Modul: Angewandte Mathematik (Bachelorstudium: Mathematik) Modul: Applications and Related Topics (Bachelorstudium: Computer Science) Modul: Applications and Related Topics (Bachelor Studienfach: Computer Science) Modul: Electives in Data Science (Masterstudium: Data Science) |
| Prüfung | Lehrveranst.-begleitend |
| Hinweise zur Prüfung | 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%). |
| An-/Abmeldung zur Prüfung | Anm.: Belegen Lehrveranstaltung; Abm.: stornieren |
| Wiederholungsprüfung | keine Wiederholungsprüfung |
| Skala | 1-6 0,5 |
| Belegen bei Nichtbestehen | beliebig wiederholbar |
| Zuständige Fakultät | Philosophisch-Naturwissenschaftliche Fakultät, studiendekanat-philnat@unibas.ch |
| Anbietende Organisationseinheit | Fachbereich Mathematik |