Seelow Lab – Bioinformatics and Translational Genetics

The main research area of the Bioinformatics and Translational Genetics group is the elucidation of monogenic diseases (genetic disorders caused by DNA mutations in a single gene). We are developing user-friendly software that can be used by non-IT specialists. This allows the physicians – who know most about the patients and their disorders – to analyse genetic data by themselves.

All our applications are free to use for academic research.

Research focus

Identification of disease-causing mutations

The advent of high-throughput DNA sequencing technologies has revolutionised the study of genetic disease. However, humans carry several millions of deviations from the human genome ‘reference’ sequence, so called DNA variants. Due to the large amounts of data, experimental analysis or even a manual assessment of the potential effects of the variants is not feasible. Therefore, bioinformatic methods have to be applied to identify the variant with the highest disease-causing potential.

We have developed several applications to help physicians and researchers in this daunting task:

HomozygosityMapper ( is aimed at the identification of disease-linked genetic regions in consanguineous families.

GeneDistiller ( is a candidate gene search engine which allows researchers to find the genes most likely to cause the disease they study.

MutationTaster ( predicts the effect of DNA variants on the protein encoded by the gene they reside in and their potential to destroy the protein’s function.

MutationDistiller ( combines GeneDistiller and MutationTaster. The effect of a DNA variant on the protein and the possible role of this protein in the pathogenesis of a specific disorders are brought together to find the most likely disease mutation in a flood of variants.

CNVinspector ( helps researchers to identify potentially disease-causing 'copy-number variants' (CNV) in the genome of patient.

ePOSSUM ( evaluates the effect of DNA variants on transcription factor binding.

RegulationSpotter ( is aimed at the user-friendly search for disease-causing mutations outwith protein-coding genes.

Further projects

Exact digital phenotyping of patients ('deep phenotyping')

Personalised medicine or precision medicine requires detailed information about a patient's disorder, i.e. the symptoms he or she shows – and those which are absent. We are developing tools to complement medical letters with an exact, machine-readable and machine-analysable description of the patient’s phenotype.


Anja Heß (

Daniela Hombach (

Dominik Seelow (

Robin Steinhaus (

Selected publications

MutationDistiller: user-driven identification of pathogenic DNA variants. Hombach D, Schuelke M, Knierim E, Ehmke N, Schwarz JM, Fischer-Zirnsak B, Seelow D. Nucleic Acids Res. 2019 May 20. pii: gkz330. doi: 10.1093/nar/gkz330.

A systematic, large-scale comparison of transcription factor binding site models. Hombach D, Schwarz JM, Robinson PN, Schuelke M, Seelow D. BMC Genomics. 2016 May 21;17:388.

MutationTaster2: mutation prediction for the deep-sequencing age. Schwarz JM, Cooper DN, Schuelke M, Seelow D. Nat Methods. 2014 Apr;11(4):361-2.

HomozygosityMapper2012 - bridging the gap between homozygosity mapping and deep sequencing.Seelow D, Schuelke M. Nucleic Acids Res. 2012 Jul;40(Web Server issue):W516-20.

The Human Phenotype Ontology: a tool for annotating and analyzing human hereditary disease. Robinson PN, Köhler S, Bauer S, Seelow D, Horn D, Mundlos S. Am J Hum Genet. 2008 Nov;83(5):610-5.