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.


Lecture: Introduction to bioinformatics data types and analysis techniques

The lecture "Introduction to bioinformatics data types and analysis techniques" is hosted by the department "Computational Biology of Infection Research" at the HZI headed by Prof. Alice McHardy.

Date: Tuesdays at 11 a.m.
Place: Remote lecture via  Zoom
Kick-off: 19th April 2022, 11 a.m.
Language: English
Modus: 14x90min lectures, lecture series with alternating teachers from BIFO
Examination: 2 block exercises at the end of the semester (exact date tba) and exam
Credits: 4 SWS = 5 ECTS

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


Bioinformatics has become an indispensable part of modern biology. Whether in the decoding of the human genome or the vaccine development for SARS-CoV-2: Bioinformatics methods play a crucial role.

The lecture "Introduction to bioinformatics data types and analysis techniques" will give a practical introduction to different algorithms and application fields for bioinformatics and especially for data generated during genome sequencing. In addition, there will be two exercises in which hands-on bioinformatics methods will be applied as well as an introduction to the programming language R, which is essential for data scientists.

The lecture is a joint lecture for the BIOMEDAS graduate school and for master students of computer science with interest in biological questions but does not require any special prior biological or computer science knowledge.

Lectures in detail:

  • Kick-off session (19.04., Adrian Fritz)
  • atabases in bioinformatics (26.04., Fernando Meyer)
  • Fundamental statistical approaches in bioinformatics (03.05, Klaus Jung)
  • Dimension reduction and clustering approaches (10.05., Klaus Jung)
  • Introduction into high-throughput data generation: optical vs. counts data (17.05., Sama Goliaei)
  • Quality control of bioinformatics data (24.05., Adrian Fritz)
  • Next generation sequencing: molecular introduction (31.05., Fernando Meyer)
  • Machine learning in bioinformatics (e.g. for biomarker detection) (07.06, Ehsaneddin Asgari)
  • Next generation sequencing: analysis of transcriptomics data (14.06., Zhi-Luo Deng)
  • Next generation sequencing: analysis of genomics data (21.06., Aideen Roddy)
  • Next generation sequencing: analysis of metagenomics / metatranscriptomics data (28.06., Adrian Fritz)
  • Next generation sequencing: analysis of single-cell data (05.07., Hadi Foroughmand)
  • Next generation sequencing: epigenomics (12.07., Aideen Roddy)
  • Various topics for next generation sequencing (19.07., Hadi Foroughmand)
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