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 https://doi.org/10.1101/104034
Steinegger, M., and Söding, J. (2017) MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nature Biotechnol., accepted. bioRxiv, https://doi.org/10.1101/079681
Söding, J. (2017) Big-data approaches to protein structure prediction. Science (perspective), 355, 248-249. https://doi.org/10.1126/science.aal4512
Siebert M. and Söding, J. (2016) Markov models consistently outperform PWMs atpredicting regulatory motifs in nucleotide sequences. Nucleic Acids Res., 44, 6055-6069. https://doi.org/10.1093/nar/gkw521
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. https://doi.org/10.1016/j.molcel.2017.02.009
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. https://doi.org/10.1038/nature13587
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. https://doi.org/10.1016/j.cell.2013.10.024
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. https://doi.org/10.1101/gr.139881.112
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. https://doi.org/10.1038/nmeth.1818
Biegert, A. and Söding, J. (2009) Sequence context-specic amino acid similarities for homology searching. Proc. Natl. Acad. Sci. USA, 106, 3770-3775. https://doi.org/10.1073/pnas.0810767106
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. https://doi.org/10.1093/nar/gki408.
Söding, J. (2005) Protein homology detection by HMM-HMM comparison. Bioinformatics, 21, 951-960. https://doi.org/10.1093/bioinformatics/bti125
(#Equal contributions. *Corresponding authors.)
