Bioinformatics and Computational Biophysics

Bioinformatics and Computational Biophysics

Daniel Hoffmann

Contact

Prof. Dr. Daniel Hoffmann


Faculty of Biology
University of Duisburg-Essen

Research
Overview

Quantitative Biology

Biology is a messy science. Its subjects - biomolecules, cells, tissues, organisms, ecosystems, etc. - are highly complex and variable. This makes it difficult to pin down laws as reliably as, say, in physics. It is therefore not surprising that biologists are fully occupied with taming their complex subjects, and with obtaining (using a minimum of mathematics) simple, qualitative results from experiments.
However, we know that living systems are essentially quantitative; e.g. it matters a lot whether you have too little or too much of a substance in an organism. If we want to account for this, we have to use quantitative mathematical and computational models of biological systems or biological data. This is exactly what we do.

In our research we are developing mathematical or computational models for biological systems. Often these models are probabilistic because biological systems are variable and not completely characterized, and probabilities are an effective way of dealing with variability. We can then infer quantitative relationships by computational methods such as Bayesian analyses.
This is a Swiss knife approach that is basically applicable to all kinds of biology. Accordingly, we have fruitful collaborations with researchers from many areas, e.g. developmental biologists, virologists, immunologists, cancer researchers, or ecologists.

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