Bioinformatics and Computational Biophysics
Daniel Hoffmann
Prof. Dr. Daniel Hoffmann
Faculty of Biology
University of Duisburg-Essen
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.