|Since August 2017||Group leader||Algorithms for reproducible bioinformatics, Institute of Human Genetics, University of Duisburg-Essen|
|August 2016 -July 2017||Researcher||Life Sciences, CWI Amsterdam|
|Since May 2016||Consultant||Myles Brown, Division of Molecular and Cellular Oncology, Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School|
|May 2016 -
|Postdoc||Alexander Schönhuth, Life Sciences, CWI Amsterdam|
|April 2015 -
|Postdoc||Shirley Liu, Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Harvard School of Public Health|
|Postdoc||Myles Brown, Division of Molecular and Cellular Oncology, Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School|
|January 2011 -
|PhD student||Sven Rahmann, Genome Informatics, University Duisburg-Essen|
|Guest member||Eli Zamir, Systems Biology of Cell Matrix Adhesion, Max-Planck-Institute of Molecular Physiology Dortmund|
A Bayesian model for single-cell transcript (differential) expression analysis on MERFISH data. The model allows to overcome systematic biases occurring with MERFISH and provides measures of uncertainty and control of the false discovery rate in a strictly Bayesian way. MERFISHtools is a corresponding command line client and analysis library written in Rust and Python. MERFISHtools is also available via Bioconda.
A distribution of bioinformatics software realized as a channel for the versatile package manager Conda.
A bioinformatics library written in the Rust language. The implementation provides state of the art solutions for common tasks in bioinformatics, focusing on stability by using comprehensive unit tests and continuous integration.
ALPACA is a variant caller for next-generation sequencing data that incorporates sample based filtering into the calling. This allows intuitive control of the false discovery rate with generic sample filtering scenarios. Further, it uses preprocessing and merging of BCF files to solve the N+1 problem: an existing study can be extended with new samples without redundant computations. After the preprocessing, the actual calling is a matter of seconds.
PEANUT is a read mapper for DNA or RNA sequence reads. By exploiting the massive parallelism of modern graphics processors and a novel index datastructure, PEANUT achieves superior speed compared to current state of the art read mappers like BWA MEM, Bowtie2 and RazerS3, while maintaining their accuracy. It thereby allows to report both only the best hits or all hits of a read. In case of reporting all hits, PEANUT is four to ten times faster than competitors.
Snakemake is a workflow engine and language. It aims to reduce the complexity of creating workflows by providing a fast and comfortable execution environment, together with a clean and modern domain specific specification language (DSL) in python style.
LibModalLogic is a JAVA implementation of Modal Logic K and Propositional Logic. Logic formulas can be build in memory, saved to and read from MathML and formatted human readable. Reasoning is implemented by the (modal) logic tableau algorithm, including dynamic backtracking for maximum performance.
TRMiner is a python tool that aims at scientific data curators. It allows to rapidly prune large collections of scientific publications to sentences relevant for a given mining goal, using a linear time matching algorithm.
Protein Hypernetworks are an approach for endowing protein networks with interaction dependencies using propositional logic. This allows refined network based predictions of protein complexes, functional importance and functional similarity.
|2013||Guest lecture "Detecting SNVs with Next-generation-Sequencing" in the course "Statistik in der Genetik", Faculty of Statistics, TU Dortmund.|
|2012||Co-supervised bachelor thesis "Rekonstruktion von Protein-Interaktionsabhängigkeiten mit dem Quine-McCluskey-Algorithmus", Bianca Patro, TU Dortmund.|
|2011||Teaching assistant for "Datenstrukturen Algorithmen und Programmierung" (DAP1), Faculty of Computer Science, TU Dortmund|
Co-supervised bachelor thesis "Konstruktion von Protein-Hypernetzwerken durch Text-Mining in der PubMed Datenbank", Michael Nimbs, TU Dortmund.
Co-supervised diploma thesis "Entwurf einer Datenstruktur für Pangenome", Christiane Küch, TU Dortmund.
|phone||+31(0)20 592 4381|
|office||Room 1.13 University Hospital Essen Virchowstr. 183 45147 Essen|
Dr. rer. nat. Johannes Köster
Institute of Human Genetics
University of Duisburg-Essen