Johannes Söding
Research Group Leader
Phone:+49 551 201-2890Fax:+49 551 201-2803

Short CV

Quantitative and Computational Biology group

  Quantitative and Computational Biology

Our group develops statistical and computational methods for analyzing data from high-throughput biological experiments. Our work is focussed on protein function and structure prediction, sequence search and assembly in metagenomics, transcription regulation, gene regulatory networks, and systems medicine.

Google scholar profile for Johannes Söding 

Selected publications:

Steinegger, M., and Soding, J. (2017) Linclust: clustering billions of sequences per day on a single server.  Under review. bioRxiv

Steinegger, M., and Söding, J. (2017) MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nature Biotechnol., accepted. bioRxiv,

Söding, J. (2017) Big-data approaches to protein structure prediction. Science (perspective), 355, 248-249.

Siebert M. and Söding, J. (2016) Markov models consistently outperform PWMs atpredicting regulatory motifs in nucleotide sequences. Nucleic Acids Res., 44, 6055-6069.

Baejen, C.,# Andreani, J.,# Torkler, P., Battaglia, S., Schwalb, B., Lidschreiber, M., Maier, K.C., Boltendahl, A., Rus, P., Esslinger, S., Söding, J.*, and Cramer, P.* (2017) Genome-wide analysis of RNA polymerase II termination at protein-coding genes. Molecular Cell 66, 38-49.e6.

Meier, A. and Söding, J. (2015) Automatic prediction of protein 3D Structures by probabilistic multi-template homology modeling. PLoS Comput. Biol., 11:e1004343. doi: 10.1371/journal.pcbi.1004343

Siebert, M. and Söding, J. (2014) Universality of core promoter motifs? Nature (Brief Commun. Arising), 511, E11–E12.

Schulz, D.#, Schwalb, B.#, Kiesel, A., Baejen, C., Torkler, P., Gagneur, J., Söding,J.* and Cramer, P.* (2013) Transcriptome surveillance by selective termination of noncoding RNA synthesis. Cell, 155, 1075-1087.

Hartmann, H., Guthohrlein, E. W., Siebert, M., Luehr, S., and Söding, J. (2013)  P-value based regulatory motif discovery using positional weight matrices. Genome Res. 23, 181-194.

Remmert, M., Biegert, A., Hauser, A., and Söding, J. (2012) HHblits: Lightning-fast iterative protein sequence searching by HMM-HMM alignment. Nat. Methods, 9, 173-175.

Biegert, A. and Söding, J. (2009) Sequence context-specic amino acid similarities for homology searching. Proc. Natl. Acad. Sci. USA, 106, 3770-3775.

Söding, J.*, Biegert, A., and Lupas, A. N. (2005) The HHpred interactive server for protein homology detection and structure prediction. Nucleic Acids Res., 33, W244-W248.

Söding, J. (2005) Protein homology detection by HMM-HMM comparison. Bioinformatics, 21, 951-960.

(#Equal contributions. *Corresponding authors.)

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