Algorithms for Computational Biology

Daniel Huson

DanielHuson23-11-2012-04 crop1
  • 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

Development and application of computational tools for long read microbiome analysis.

Selected Reading

1) 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).

2) 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.

3) Buchfink, B., C. Xi and DH Huson (2015), Fast and sensitive protein alignment using DIAMOND, Nature Methods, 12, 59–60. .