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 inference 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.

Lecturer

Prof. Dr. Hans-Peter Lenhof

Teaching Assistants

Prerequisites Important

Conditions for Certificate

Registration

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.

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
1 Bayesian Networks Deepti Mittal Tim Kehl
2 Causality from Time Series
3 Causal Reasoning
4 Supervised Network Inference Muhammad Raheel Farooq Tim Kehl
5 Incorporating Prior Knowledge Venkata Praveen Kumar Velisetty Lara Schneider
6 Structural Equation Modeling
7 PC Algorithm Nadia Ashraf Lara Schneider
8 Gaussian Graphical Models
First Meeting
Friday, 10.07.2015, 4:30 pm, Building E2.1, Room 406
Essay Deadline
Friday, 04.09.2015 11:59 pm
Slides Deadline
Friday, 02.10.2015, 11:59 pm
Talks
Monday, 12.10.2015, 10:00 am - 11:00 am, Building E2.1, Room 406

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)