Contact
Hannoversche Straße 28
10115 Berlin, Deutschland
The expression of genes is tightly controlled on several levels — a large number of protein and RNA factors and DNA and RNA sequence elements enable the precise regulation of interacting gene products. It is a key challenge to decipher these complex networks of players and interactions, and to understand biology via integrated, global approaches.
To this end, our lab develops and applies genomics and computational approaches to understand mechanisms of gene regulation in eukaryotic organisms. Computational biology, and machine learning in particular, has become indispensable to analyze and ultimately make sense of large-scale data sets that look at the phenomenon of gene regulation from different angles.
Our long term goal is to investigate how regulatory networks enable the correct development of complex organisms, with their multitude of cell types that carry out different functions despite the same genome. This will help us to understand the impact of sequence variation on biological functions and disease.
Visting students, Master's students, Bachelor students...
Former undergraduate/rotation students at Duke...
We are an integrated interdisciplinary lab, whose members aim to understand the gene regulatory code through high throughput experiments and computational approaches. To this end, we want to find out…
We adapt and apply genomics approaches, and collaborate extensively, to obtain new types of molecular data at ever increasing resolution. We develop new computational methods to analyze and integrate new types of data. We design interpretable, predictive machine learning methods — from sparse linear models to deep neural networks — to understand different mechanisms of gene regulation on the DNA and RNA level. These days, our focus is on:
As computational lab, we develop a lot of new software that we make available to the scientific community.
Prediction of coding and non-coding genes
Promoter and enhancer analysis
TF target site identification
ChIP/CLIP analysis
miRNA target prediction
Ribosome profiling
Regulatory network topology
Gene expression imaging
Analysis of RNA-binding proteins
Identification of RNA editing events
Best practice tools for sequencing
Promoter and enhancer analysis
TF target site identification
ChIP/CLIP analysis
Ribosome profiling
Analysis of RNA-binding proteins
Machine learning and single cell genomics
Einführung in die Programmierung und Bioinformatik (w/Pawel Romanczuk, summer semester)
Computational Analysis and Interpretation of High-throughput Data (w/Laleh Haghverdi and Altuna Akalin, winter semester)
Uwe describes the lab's research at Latest Thinking (2018)
A Nature Methods feature on our hunt for meaningful non-protein-coding genes (2018)
Uwe and Philipp led a Meetup at re:publica 2018
Dubravka (Dusa) hosted artist Emilia Tikka to learn about CRISPR-based iPS cells for her piece Aeon (2018). Read the feature in Nature!
Uwe was interviewed for a Nature feature on the research environment in Germany (2019)
Uwe was on stage at Berliner Ensemble's Galileo Galilei to discuss machine learning as part of a "science meets theater" day (2019)
Dubravka and Uwe presented at Children of Doom (2019). Watch the videos here and here!!
The lab was at Lange Nacht der WIssenschaften 2019!
During Berlin Science Week 2020, Karla Stereochemistry performed in the lab -- and Uwe was interviewed for Radio Arty on FluxFM!
For available PhD and postdoc positions, please get in touch with Uwe!
Interested in working on a project for your Bachelor or Master's thesis ? Contact Uwe or Scott!