Computational Biology for Infection Research

The Department of “Computational Biology for Infection Research” studies the human microbiome, viral and bacterial pathogens, and human cell lineages within individual patients by analysis of large-scale biological and epidemiological data sets with computational techniques. Focusing on high throughput meta’omics, population genomic and single cell sequencing data, we produce testable hypotheses, such as sets of key sites or relevant genes associated with the presence of a disease, of antibiotic resistance or pathogenic evasion of immune defense. We interact with experimental collaborators to verify our findings and to promote their translation into medical treatment or diagnosis procedures. To achieve its research goals, the department also develops novel algorithms and software.



Web Applications

Traitar is a web service for phenotyping bacteria based on their genome sequences. 

PhyloPythiaS+ - a self-training method for the rapid reconstruction of low-ranking taxonomic bins from metagenomes

PhyloPythiaS  - the PhyloPythiaS Web Server for Taxonomic Assignment of Metagenome Sequences.

Taxator-tk  performs taxonomic sequence assignment by fast approximate determination of evolutionary neighbors from sequence similarities.

AdaPatch  is a method for detecting positively selected patches of sites on the surface of viral proteins, which are likely candidates for being relevant for adaptive evolution.

Software Downloads

Software implementing the group’s research can be downloaded here or on GitHub at, such as

SDplots: software for the detection of selective sweeps to monitor the adaptation of influenza A viruses

SDplots VaccineUpdates: results of the bi-annual vaccine strain prediction for influenza A viruses

PatchDetection: software for the detection of protein patches under positive selection

Phylogeography: software for phylogeographical reconstruction to infer origin and spread routes of viral pathogen outbreaks

FrechetTreeDistances: distances between phylogeographic reconstructions across tree topologies.

DiTaxa: nucleotide-pair encoding of 16S rRNA sequences for host phenotype and biomarker detection

CAMISIM: Simulating metagenomes and microbial communities

AMBER: Assessment of Metagenome BinnERs

OPAL: Open-community Profiling Assessment tooL

CAMITAX: Taxon labels for microbial genomes

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