ZMB Member Daniel Hoffmann
ZMB Member
Daniel Hoffmann
Next ZMB-Member
Prof. Dr. Daniel Hoffmann
Faculty of Biology
University of Duisburg-Essen
Universitätsstr. 2
45141 Essen
- +49 201 183 4391
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- ZMB Research Program
Molecular and Chemical Cell Biology
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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Selected Publications
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BAYAS : simplifying access to Bayesian analysis for biologistsIn: Bioinformatics , Vol. 41 2025, Nr. 6, btaf276DOI (Open Access)
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HBV shows different levels of adaptation to HLA class I-associated selection pressure correlating with markers of replicationIn: Journal of Hepatology , Vol. 82 2025, Nr. 5, pp. 805 – 815DOI (Open Access)
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HAMdetector : A Bayesian regression model that integrates information to detect HLA-associated mutationsIn: Bioinformatics , Vol. 38 2022, Nr. 9, pp. 2428 – 2436DOI (Open Access)
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Specific inhibition of the Survivin–CRM1 interaction by peptide-modified molecular tweezersIn: Nature Communications , Vol. 12 2021, Nr. 1, pp. 1505DOI, Online Full Text (Open Access)
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IgGeneUsage : differential gene usage in immune repertoiresIn: Bioinformatics , Vol. 36 2020, Nr. 11, pp. 3590 – 3591
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A network of trans-cortical capillaries as mainstay for blood circulation in long bonesIn: Nature Metabolism , Vol. 1 2019, Nr. 2, pp. 236 – 250DOI (Open Access)
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Mutations in Hepatitis D Virus Allow It to Escape Detection by CD8⁺ T Cells and Evolve at the Population LevelIn: Gastroenterology , Vol. 156 2019, Nr. 6, pp. 1820 – 1833DOI (Open Access)
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Viral escape contributes to the failure of hepatitis D virus-specific CD8+ T-cells and drives evolution of HDVIn: Journal of Hepatology , Vol. 70 2019, Nr. Suppl. 1, pp. e21
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Biased IGH VDJ gene repertoire and clonal expansions in B cells of chronically hepatitis C virus–infected individualsIn: Blood , Vol. 131 2018, Nr. 5, pp. 546 – 557DOI (Open Access)
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Adaptation of the Hepatitis B Virus Core Protein to CD8+ T-Cell Selection PressureIn: Hepatology , Vol. 62 2015, Nr. 1, pp. 47 – 56DOI (Open Access)
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HLA-B*27 is protective against HCV genotype 1 and 3 and associated with targeting of distinct genotype-specific CD8(+) cell epitopesIn: Journal of Hepatology , Vol. 60 2014, Nr. Suppl. 1, pp. 140
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Backbone rigidity and static presentation of guanidinium groups increases cellular uptake of arginine-rich cell-penetrating peptidesIn: Nature Communications , Vol. 2 2011, pp. 453DOI (Open Access)
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CD8+ T-Cell Response Promotes Evolution of Hepatitis C Virus Nonstructural ProteinsIn: Gastroenterology , Vol. 140 2011, Nr. 7, pp. 2064 – 2073
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Computational methods for the design of effective therapies against drug resistant HIV strainsIn: Bioinformatics , Vol. 21 2005, Nr. 21, pp. 3943 – 3950DOI (Open Access)
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Mtreemix : A software package for learning and using mixture models of mutagenetic treesIn: Bioinformatics , Vol. 21 2005, Nr. 9, pp. 2106 – 2107DOI (Open Access)
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Methods for optimizing antiviral combination therapiesIn: Bioinformatics , Vol. 19 2003, Nr. Suppl 1, pp. i16 – i25DOI (Open Access)
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Web Site : The Protein Information ResourceIn: Angewandte Chemie International Edition , Vol. 41 2002, Nr. 6, pp. 1075 – 1075
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Strain-Induced “Band Flips” in Cyclodecaamylose and Higher HomologuesIn: Angewandte Chemie International Edition , Vol. 37 1998, Nr. 5
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Structures of the Common Cyclodextrins and Their Larger Analogues -- Beyond the DoughnuIn: Chemical Reviews , Vol. 98 1998, pp. 1787 – 1802
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Structures of the common cyclodextrins and their larger analogues : beyond the doughnutIn: Chemical Reviews , Vol. 98 1998, Nr. 5, pp. 1787 – 1802