Topics in Computational Biology WS17/18

Lecturers:Fabian Theis      Turid Frahnow 
Tel.: +49 89 2891-7961Tel.: +49 89 3187-4844  
E-mail: theisnoSp@m@ma.tum.de   E-mail: turid.frahnownoSp@m@tum.de  

 

 

Room:TUM, 03.06.011 seminar room (M6/M8) (5606.03.011)
Date & Time:     Wednesday, 4.15 pm - 5.45 pm
Prerequisites:Bachelor in mathematics, bioinformatics, statistics or related fields.
ECTS:3
Number of participants:< 50
Language:      English

 

Topic: 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 (ICB), Helmholtz Center Munich, Ingolstädter Landstraße 1, 85764 Neuherberg

Prerequisites: Bachelor in mathematics, bioinformatics, statistics and related fields.

Aims of the course: After the successful completion of the module, the participants

  • understand a selection of methods used in computational biology
  • understand advantages and disadvantages of the introduced methods
  • can evaluate which methods can be used to approach a given problem

Modalities:

  • 1 Introductory lecture
  • 5 lectures introduce 5 project topics
  • team project work
  • presentation of project work (@TUM)

Schedule of the course:

18.10.2017 - Carsten Marr - "Introduction"
25.10.2017 - Jan Hasenauer - "Statistical inference for dynamical biological systems"
08.11.2017 - Carsten Marr - "Models of Stem Cell Decision Making"
15.11.2017 - Fabian Theis - "Machine learning in single cell transcriptomics"
22.11.2017 - Antonio Scialdone - "Quantitative models of transcriptional gene regulation"
29.11.2017 - Maria Colome-Tatche - "Hidden Markov Models for the analysis of epigenomics data"

Dec'17 - Feb'18 - Project work
02.02.18, 23:59 - Report submission deadline
07.02.2018 - Project presentations (@TUM)

Grading modalities / Presentations / Report: 

Each group should hand in a report with three to five pages. At the end of the report author contributions should be described with a few sentences (as e.g. in Nature papers). It is okay if two groups with the same topic submit the same report of increased length. The deadline for submission of the report is Friday 2nd Feb 2018, 23:59, so that supervisors have enough time to correct the report before the presentation. Please use the templates in TUM Moodle.

On the 07th Feb 2018, we will host presentations at the TUM (starting at 16:15 (be there at 16:00).
Each group should give a presentation in which each member actively participates for about 5 minutes. Presentations should last either 10 min (group <=2 members), 15 min (group with 3 members), or 20 min (group with 4 members). There will be a session directly after the presentation with questions for all group members. Each participant will be graded based on her/his performance during presentation and discussion.

The final grade will be the average of the report and presentation grades.

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