Daniel Huson

Algorithms for Computational Biology

University of Tübingen
Faculty in: IMPRS

Vita

Habilitation in mathematics, University of Bielefeld, 1997
Post-doc Princeton University and University of Pennsylvania, 1997-99
Senior Staff Scientist, Celera Genomics, Rockville, 1999-2002
Professor of Algorithms in Bioinformatics, University of Tübingen, since 2002
Visiting Professor at the National University of Singapore, 2015-19

Research Interest
Most of what is known about microbes is based on studying them in culture, although they naturally live in complex communities. Metagenomics aims at understanding microbial ecology using next-generation sequencing of DNA and cDNA sequences. The research of our group is focused on the development and application of new methods in computational biology, in particular for microbiome analysis, but also for genomics and phylogenetics. Popular tools developed by this lab include MEGAN, Diamond, MetaSim, Dendroscope and SplitsTree.

Available PhD Projects in the IMPRS

Currently not recruiting PhD students

Selected Reading

Huson, DH, Albrecht, B, Bagci, C, Bessarab, I, Gorska, A, Jolic D, et al. (2018). MEGAN-LR: New algorithms allow accurate binning and easy interactive exploration of metagenomic long reads and contigs Biology Direct, 13(6).
Huson, DH, Beier, S, Flade, I, Gorska, A, El-Hadidi, M, et al. (2016). MEGAN Community Edition - Interactive exploration and analysis of large-scale microbiome sequencing data, PLoS Comput Biol, 12(6):e1004957.
Buchfink, B., C. Xi and DH Huson (2015), Fast and sensitive protein alignment using DIAMOND, Nature Methods, 12, 59–60.