Physics Department, TUM | Course 0000002414 in WS 2019/20

General Data

Course Type

lecture

Semester Weekly Hours

2 SWS

Organisational Unit

Research Department Mathematics Centre

Lecturers

Carsten Marr
Tingying Peng
Fabian Theis

Dates

Wed, 14:15–15:45, MI 03.06.011

iCalendar

	Date and Time	Room and Remark
	Wed, 2019-10-16, 14:15–15:45	Boltzmannstr. 3
	Wed, 2019-10-23, 14:15–15:45	Boltzmannstr. 3
	Wed, 2019-10-30, 14:15–15:45	Boltzmannstr. 3
	Wed, 2019-11-06, 14:15–15:45	Boltzmannstr. 3
	Wed, 2019-11-13, 14:15–15:45	Boltzmannstr. 3
	Wed, 2019-11-20, 14:15–15:45	Boltzmannstr. 3
	Wed, 2019-11-27, 14:15–15:45	Boltzmannstr. 3
	Wed, 2019-12-04, 14:15–15:45	Boltzmannstr. 3
	Wed, 2019-12-11, 14:15–15:45	Boltzmannstr. 3
	Wed, 2019-12-18, 14:15–15:45	Boltzmannstr. 3
	Wed, 2020-01-08, 14:15–15:45	Boltzmannstr. 3
	Wed, 2020-01-15, 14:15–15:45	Boltzmannstr. 3
	Wed, 2020-01-22, 14:15–15:45	Boltzmannstr. 3
	Wed, 2020-01-29, 14:15–15:45	Boltzmannstr. 3
	Wed, 2020-02-05, 14:15–15:45	Boltzmannstr. 3

Assignment to Modules

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)
This module is included in the following catalogs:
- Elective Modules Natural Sciences in the Master Program Matter to Life

Further Information

Courses are together with exams the building blocks for modules. Please keep in mind that information on the contents, learning outcomes and, especially examination conditions are given on the module level only – see section "Assignment to Modules" above.

additional remarks	In all fields of life sciences, ranging from yeast strain optimization for brewing (→ bioprocess engineering) over stem cell research (→ basic biology) to the treatment of disease (→ medicine), computational methods are employed to deepen our understanding of the respective biological processes/system. As the range of biological questions approached using computational biology is rather broad, the number of different methods applied in this field is tremendous. Commonly used tools include gene sequence analysis, image analysis, statistical network modeling and dynamic pathway modeling. All of these tools span one or more fields of mathematics, e.g., statistics, differential equations and optimization. This lecture series aims at providing the participants with an overview about different fields of computational biology and the methods used in this field. To complement the theoretical part, concrete application and ongoing research projects will be presented. The individual lectures of the lecture series will be taught by persons from the: - M12 Biomathematics, Center of Mathematical Sciences, TUM - Institute of Computational Biology, Helmholtz Center Munich
Links	E-Learning course (e. g. Moodle) TUMonline entry

additional remarks

In all fields of life sciences, ranging from yeast strain optimization for brewing (→ bioprocess engineering) over stem cell research (→ basic biology) to the treatment of disease (→ medicine), computational methods are employed to deepen our understanding of the respective biological processes/system. As the range of biological questions approached using computational biology is rather broad, the number of different methods applied in this field is tremendous. Commonly used tools include gene sequence analysis, image analysis, statistical network modeling and dynamic pathway modeling. All of these tools span one or more fields of mathematics, e.g., statistics, differential equations and optimization. This lecture series aims at providing the participants with an overview about different fields of computational biology and the methods used in this field. To complement the theoretical part, concrete application and ongoing research projects will be presented. The individual lectures of the lecture series will be taught by persons from the: - M12 Biomathematics, Center of Mathematical Sciences, TUM - Institute of Computational Biology, Helmholtz Center Munich

Links

E-Learning course (e. g. Moodle)
TUMonline entry

Equivalent Courses (e. g. in other semesters)

Semester	Title	Lecturers	Dates
WS 2018/9	Topics in Computational Biology	Marr, C. Peng, T. Theis, F.	Wed, 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. Responsible/Coordination: 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.

This website is no longer updated.

Selected Topics in Machine Learning & Modelling in Biology [MA5607]

Course 0000002414 in WS 2019/20

General Data

Assignment to Modules

Further Information

Equivalent Courses (e. g. in other semesters)