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55662-01 - Vorlesung: Applied Mathematics and Informatics in Drug Discovery 2 KP

Semester Herbstsemester 2022
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 www.amidd.ch

 

Teilnahmebedingungen 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.
Anmeldung zur Lehrveranstaltung Due to the coronavirus pandemic, the course in fall semester 2021 will take place online by Zoom. To attend, join the meeting with this link: https://unibas.zoom.us/j/68803401669. The passcode required to join the meeting is shared among registered students with emails.
Unterrichtssprache Englisch
Einsatz digitaler Medien kein spezifischer Einsatz
HörerInnen willkommen

 

Intervall wöchentlich
Datum 23.09.2022 – 23.12.2022
Zeit Freitag, 12.15-14.00 Spiegelgasse 5, Seminarraum 05.002
Datum Zeit Raum
Freitag 23.09.2022 12.15-14.00 Uhr Spiegelgasse 5, Seminarraum 05.002
Freitag 30.09.2022 12.15-14.00 Uhr Spiegelgasse 5, Seminarraum 05.002
Freitag 07.10.2022 12.15-14.00 Uhr Spiegelgasse 5, Seminarraum 05.002
Freitag 14.10.2022 12.15-14.00 Uhr Spiegelgasse 5, Seminarraum 05.002
Freitag 21.10.2022 12.15-14.00 Uhr Spiegelgasse 5, Seminarraum 05.002
Freitag 28.10.2022 12.15-14.00 Uhr Spiegelgasse 5, Seminarraum 05.002
Freitag 04.11.2022 12.15-14.00 Uhr Spiegelgasse 5, Seminarraum 05.002
Freitag 11.11.2022 12.15-14.00 Uhr Spiegelgasse 5, Seminarraum 05.002
Freitag 18.11.2022 12.15-14.00 Uhr Kollegienhaus, Hörsaal 120
Freitag 25.11.2022 12.15-14.00 Uhr Dies Academicus
Freitag 02.12.2022 12.15-14.00 Uhr Spiegelgasse 5, Seminarraum 05.002
Freitag 09.12.2022 12.15-14.00 Uhr Spiegelgasse 5, Seminarraum 05.002
Freitag 16.12.2022 12.15-14.00 Uhr Spiegelgasse 5, Seminarraum 05.002
Freitag 23.12.2022 12.15-14.00 Uhr Spiegelgasse 5, Seminarraum 05.002
Module Modul: Angewandte Mathematik (Bachelorstudium: Mathematik)
Modul: Applications and Related Topics (Bachelor Studienfach Computer Science)
Modul: Applications and Related Topics (Bachelorstudium: Computer Science)
Modul: Electives in Data Science (Masterstudium: Data Science)
Leistungsüberprüfung Lehrveranst.-begleitend
Hinweise zur Leistungsüberprüfung Scores will be given in scale 1-6 by 0.5, by participation (20%), near-end-term presentation (30%), and end-term project work (50%).
An-/Abmeldung zur Leistungsüberprüfung An-/Abmelden: Belegen resp. Stornieren der Belegung via MOnA
Wiederholungsprüfung keine Wiederholungsprüfung
Skala 1-6 0,5
Wiederholtes Belegen beliebig wiederholbar
Zuständige Fakultät Philosophisch-Naturwissenschaftliche Fakultät, studiendekanat-philnat@unibas.ch
Anbietende Organisationseinheit Fachbereich Mathematik

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