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.
Leader
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 github.com/hzi-bifo, 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