Tim Schäfer -- rcmd.org/ts/

current work || projects || publications || contact

This is the professional website of Dr. Tim Schäfer. I am a bioinformatician and currently a postdoc in computational neuroimaging at University Hospital Frankfurt. I finished my doctorate in bioinformatics at the Department of Molecular Bioinformatics (group of Prof. Dr. Ina Koch) at Goethe-University Frankfurt in November 2016. I also worked in the industry as a software engineer, system administrator, and IT trainer. I have listed some previous work below, and you can find some of my source code on my github profile. In my spare time I enjoy rock climbing and digital photography.

Current work

In 2018, I started a postdoc position in Computational Neuroimaging at University Hospital Frankfurt, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy in the group of Prof Christine Ecker. We use magnetic resonance imaging in combination with computational methods to uncover the mechanisms of mental disorders.

Previous projects

I finished my doctorate in 2016 and mainly worked on the following two projects in the fields of digital pathology and structural biology:

Digital pathology: The spatial distribution of immune cells in Hodgkin lymphoma

In this project, I worked on the analysis of Hodgkin lymphoma, a cancer of the lymphatic system, based on high-resolution images. We were interested in better understanding the way tumour cells interact with their environment, communicate and spread through the lymphatic system. We implemented a digital image analysis pipeline to perform cell detection, description and classification. We used graphs to model and compare spatial cell distributions in different Hodgkin lymphoma subtypes as well as lymphadenitis. This is a collaboration with the Senckenberg Institute of Pathology at University Hospital Frankfurt.

Hodgkin lymphoma cell graph

Part of a whole slide image from a Hodgkin lymphoma case. Cell nuclei are stained in blue, and CD30+ cells in red. A cell graph is displayed as an overlay. Each vertex represents a cell detected by our imaging pipeline. Edges are added between cells which are close to each other. The graphs can be used to quantify clustering and to compare cell distributions.

Structural biology: The new Protein Topology Graph Library (PTGL) webserver

My diploma thesis dealt with modeling protein structure topologies by graph-theoretical methods. A part of the thesis was the development of the Visualization of Protein Ligand Graphs (VPLG) software. VPLG computes and visualizes protein ligand graphs. It works on the super-secondary structure level and uses the atom coordinates from PDB files and the SSE assignments of the DSSP algorithm. The graphs can be saved to a database or exported in standard graph formats for further analysis. VPLG is free software and available from the project websites at Sourceforge and GitHub. It powers the PTGL protein topology database, a web server which also supports motif detection and other advanced queries based on the graphs computed for all proteins of the RCSB Protein Data Bank.

Protein structure

From 3D atom data to protein graph. The 3D atom coordinates and the secondary structure assignments are used to compute contacts between secondary structure elements (SSEs). In the final cell graph, each vertex represents an SSE, and edges model spatial contacts and relative spatial orientations between SSEs.


Journal Articles (Peer reviewed)

Other Articles (Non-Peer Reviewed)

Conference Talks

Posters and Conferences


It's easiest to contact me via email. My address is:


current work || projects || publications || contact