Computational Biology of 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

Seminar: Hunting SARS-CoV-2

The seminar "Hunting SARS-CoV-2" is hosted by the department "Computational Biology of Infection Research" at the HZI headed by Prof. Alice McHardy.

Kick-off Meeting: 5th October 2021, 1 p.m.
Room Kick-off Meeting: BRICS, room 207 (or remote in case the hunter becomes the hunted)
Date: one day at the end of semester break
Room seminar: tba
Max. number of participants: 10
Language: English
Modus: 30 minutes of presentation (with discussion) + 3-5 pages summary 
Designated for Bachelor and Master Students of Computer Science

In case you have questions about the seminar, feel free to contact Adrian Fritz.

Description

We all have been hit hard by the – as of today still ongoing – SARS-CoV-2 pandemic. Since day one of the pandemic, bioinformatic methods have been employed to hunt and fight the virus and the pandemic. This seminar gives an overview of some of the angles where bioinformatics helped in identifying the virus, developing vaccines and fighting the disease, i.e. viral sequencing, epidemiology, and drug design.

Topics

  • Detection and Annotation
    ◦    Viral sequencing
    ◦    Viral annotation
  • Tracking and epidemiology
    ◦    Typification of SARS-CoV-2
    ◦    Phylogeographics
    ◦    Epidemiological Modelling
  • Drug design
    ◦    Identifying potential SARS-CoV-2 drugs
    ◦    Designing a mRNA vaccine
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