Selected Topics in Machine Learning & Modelling in Biology [MA5607]
Lehrveranstaltung 0000002414 im WS 2019/20
Basisdaten
| LV-Art | Vorlesung |
|---|---|
| Umfang | 2 SWS |
| betreuende Organisation | Zentrum Mathematik |
| Dozent(inn)en |
Carsten Marr Tingying Peng Fabian Theis |
| Termine |
Mi, 14:15–15:45, MI 03.06.011 |
Zuordnung zu Modulen
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MA5607: Topics in Computational Biology (Selected Topics in Machine Learning and Modelling in Biology) / Topics in Computational Biology (Selected Topics in Machine Learning and Modelling in Biology)
Dieses Modul ist in den folgenden Katalogen enthalten:- Wahlmodule Naturwissenschaften im Masterstudiengang Matter to Life
weitere Informationen
Lehrveranstaltungen sind neben Prüfungen Bausteine von Modulen. Beachten Sie daher, dass Sie Informationen zu den Lehrinhalten und insbesondere zu Prüfungs- und Studienleistungen in der Regel nur auf Modulebene erhalten können (siehe Abschnitt "Zuordnung zu Modulen" oben).
| ergänzende Hinweise | In all fields of life sciences, ranging from the analysis of genomic data over stem cell research to the treatment of disease, computational methods are employed to deepen our understanding of the respective biological processes and make predictions about the system’s dynamics. As the range of biological questions approached with computational biology is extremely broad, the number of different methods applied is likewise tremendous. In this lecture, we will give an overview of commonly used tools in computational biology, including gene sequence analysis, image computing, statistical network approaches and dynamic pathway modelling. In particular, we will introduce recent applications of deep learning to address biological questions. In parallel to the lecture, we offer an exercise course that gives the students hands-on experience in computational analyses and sharpens their analytic and programming skills. Topics includes: -Statistical inference for dynamical biological systems -Models of Stem Cell Decision Making -Quantitative models of transcriptional gene regulation -Hidden Markov Models for the analysis of epigenomics data -Polygenic Risk Analysis -Imputing single-cell gene expression -Deep learning based bioimage processing |
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| Links |
E-Learning-Kurs (z. B. Moodle) TUMonline-Eintrag |
Gleiche Lehrveranstaltungen (z. B. in anderen Semestern)
| Semester | Titel | Dozent(en) | Termine |
|---|---|---|---|
| WS 2018/9 | Topics in Computational Biology | Marr, C. Peng, T. Theis, F. |
Mi, 14:00–16:00, MI 02.06.011 |
| WS 2017/8 | Topics in Computational Biology | Theis, F. | |
| WS 2016/7 | Topics in Computational Biology |
Theis, F.
Leitung/Koordination: Peng, T. |
|
| WS 2015/6 | Topics in Computational Biology | Theis, F. | |
| WS 2014/5 | Topics in Computational Biology | Theis, F. | |
| WS 2013/4 | Topics in Computational Biology | Hasenauer, J. Theis, F. |