Covered Topics

In this seminar you will learn how biological networks can be inferred from data. We focus on the task of inferring so-called causal networks that provide the capabilities to check and deduce hypothesis about the behaviour of biological systems under outer influences. To this end we discuss efficient models and robust inferrence algorithms.

As the discussed models are deeply rooted in probability theory and statistics a solid background in both fields is mandatory.

The seminar will be held as a block seminar the week before the lectures start.


Prof. Dr. Hans-Peter Lenhof

Teaching Assistants

Prerequisites Important

Conditions for Certificate


In order to participate in the seminar you are required to attend the first meeting. There the topics are briefly discussed and distributed. No prior registration or reservation is possible. Compulsatory registration after topic allocation till 25.07.2014 HERE.

Please inform yourself about the presented topics in order to ensure that you will get a topic that is to your liking and suits your abilities.

# Topic Speaker Supervisor
1 Bayesian Networks Christina Kiefer Patrick Trampert
2 Causality from Time Series
3 Causal Reasoning
4 Supervised Network Inference
5 Incorporating Prior Knowledge
6 Structural Equation Modeling
7 PC Algorithm Sebastian Keller Patrick Trampert
8 Gaussian Graphical Models
First Meeting
Friday, 11.07.2014, 4:30 pm, Building E2.1, Room 406
Draft Deadline
Thursday, 18.09.2014, 11:59 pm
Thursday, 16.10.2014, 10:00 am, Building E2.1, Room 406
Essay Deadline
Thursday, 23.10.2014 11:59 pm

Checklist for slides

Checklist for report

Supplementary material

  1. How to give a scientific presentation (Susan McConnell) PDF PPT
  2. The Craft of Scientific Presentations (Michael Alley)