Publications of J. Söding

Luebben, A. V.; Bender, D.; Becker, S.; Crowther, L. M.; Erven, I.; Hofmann, K.; Söding, J.; Klemp, H.; Bellotti, C.; Stäuble, A. et al.; Qiu, T.; Kathayat, R. S.; Dickinson, B. C.; Gärtner, J.; Sheldrick, G. M.; Krätzner, R.; Steinfeld, R.: Cln5 represents a new type of cysteine-basedS-depalmitoylase linked to neurodegeneration. Science Advances 8 (15), eabj8633 (2022)

Zhang, R.; Mirdita, M.; Levy Karin, E.; Norroy, C.; Galiez, C.; Söding, J.: SpacePHARER: sensitive identification of phages from CRISPR spacers in prokaryotic hosts. Bioinformatics 37 (19), pp. 3364 - 3366 (2021)

Mirdita, M.; Steinegger, M.; Breitwieser, F.; Söding, J.; Levy Karin, E.: Fast and sensitive taxonomic assignment to metagenomic contigs. Bioinformatics 37 (18), pp. 3029 - 3031 (2021)

Banerjee, S.; Simonetti, F.L.; Detrois, K. E.; Kaphle, A.; Mitra, R.; Nagial, R.; Söding, J.: Tejaas: reverse regression increases power for detecting trans-eQTLs. Genome Biology 22, 142 (2021)

Ge, W.; Meier, M.; Roth, C.; Söding, J.: Bayesian Markov models improve the prediction of binding motifs beyond first order. NAR: Genomics and Bioinformatics 3 (2), lquab026 (2021)

Choi, J.; Lysakovskaia, K.; Stik, G.; Demel, C.; Söding, J.; Tian, T. V.; Graf, T.; Cramer, P.: Evidence for additive and synergistic action of mammalian enhancers during cell fate determination. eLife 10, e65381 (2021)

Zhao, B.; Katuwawala, A.; Oldfield, C. J.; Dunker, A. K.; Faraggi, E.; Gsponer, J.; Kloczkowski, A.; Malhis, N.; Mirdita, M.; Obradovic, Z. et al.; Soding, J.; Steinegger, M.; Zhou, Y.; Kurgan, L.: DescribePROT: database of amino acid-level protein structure and function predictions. Nucleic Acids Research 49 (D1), pp. D298 - D308 (2021)

Gabler, F.; Nam, S.-Z.; Till, S.; Mirdita, M.; Steinegger, M.; Söding, J.; Lupas, A. N.; Alva, V.: Protein sequence analysis using the MPI Bioinformatics Toolkit. Current Protocols in Bioinformatics 72 (1), e108 (2020)

Erijman, A.; Kozlowski, L.; Sohrabi-Jahromi, S.; Fishburn, J.; Warfield, L.; Schreiber, J.; Noble, W. S.; Söding, J.; Hahn, S.: A high-throughput screen for transcription activation domains reveals their sequence features and permits prediction by deep learning (Correction). Molecular Cell 79 (6), p. 1066 (2020)

Erijman, A.; Kozlowski, L. P.; Sohrabi-Jahromi, S.; Fishburn, J.; Warfield, L.; Schreiber, J.; Noble, W. S.; Söding, J.; Hahn, S.: A high-throughput screen for transcription activation domains reveals their sequence features and permits prediction by deep learning. Molecular Cell 78 (5), pp. 890 - 902.e6 (2020)

Levy Karin, E.; Mirdita, M.; Söding, J.: MetaEuk—sensitive, high-throughput gene discovery, and annotation for large-scale eukaryotic metagenomics. Microbiome 8, 48 (2020)

Söding, J.; Zwicker, D.; Sohrabi-Jahromi, S.; Boehning, M.; Kirschbaum, J.: Mechanisms for active regulation of biomolecular condensates. Trends in Cell Biology 30 (1), pp. 4 - 14 (2020)

Parra, R. G.; Papadopoulos, N.; Ahumada-Arranz, L.; El Kholtei, J.; Mottelson, N.; Horokhovsky, Y.; Treutlein, B.; Söding, J.: Reconstructing complex lineage trees from scRNA-seq data using MERLoT. Nucleic Acids Research 47 (17), pp. 8961 - 8974 (2019)

Papadopoulos, N.; Parra, R. G.; Söding, J.: PROSSTT: Probabilistic simulation of single-cell RNA-seq data for complex differentiation processes. Bioinformatics 35 (18), pp. 3517 - 3519 (2019)

Steinegger, M.; Meier, M.; Mirdita, M.; Vöhringer, H.; Haunsberger, S. J.; Söding, J.: HH-suite3 for fast remote homology detection and deep protein annotation. BMC Bioinformatics 20 (1), 473 (2019)

Mirdita, M.; Steinegger, M.; Söding, J.: MMseqs2 desktop and local web server app for fast, interactive sequence searches. Bioinformatics 35 (16), pp. 2856 - 2858 (2019)

Ukmar-Godec, T.; Hutten, S.; Grieshop, M. P.; Rezaei-Ghaleh, N.; Cima-Omori, M. O.; Biernat, J.; Mandelkow, E.; Söding, J.; Dormann, D.; Zweckstetter, M.: Lysine/RNA-interactions drive and regulate biomolecular condensation. Nature Communications 10 (1), 2909 (2019)

Steinegger, M.; Mirdita, M.; Söding, J.: Protein-level assembly increases protein sequence recovery from metagenomic samples manyfold. Nature Methods 16, pp. 603 - 606 (2019)

Sohrabi-Jahromi, S.; Hofmann, K. B.; Boltendahl, A.; Roth, C.; Gressel, S.; Baejen, C.; Söding, J.; Cramer, P.: Transcriptome maps of general eukaryotic RNA degradation factors. eLife 8, e47040 (2019)

Banerjee, S.; Zeng, L.; Schunkert, H.; Söding, J.: Bayesian multiple logistic regression for case-control GWAS. PLoS Genetics 14 (12), e1007856. (2018)