J
Johannes Söding
Researcher at Max Planck Society
Publications - 121
Citations - 34018
Johannes Söding is an academic researcher from Max Planck Society. The author has contributed to research in topics: Multiple sequence alignment & Protein structure prediction. The author has an hindex of 56, co-authored 117 publications receiving 26601 citations. Previous affiliations of Johannes Söding include Ludwig Maximilian University of Munich & Protein Sciences.
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Journal ArticleDOI
Fast, scalable generation of high‐quality protein multiple sequence alignments using Clustal Omega
Fabian Sievers,Andreas Wilm,David Dineen,Toby J. Gibson,Kevin Karplus,Weizhong Li,Rodrigo Lopez,Hamish McWilliam,Michael Remmert,Johannes Söding,Julie D. Thompson,Desmond G. Higgins +11 more
TL;DR: A new program called Clustal Omega is described, which can align virtually any number of protein sequences quickly and that delivers accurate alignments, and which outperforms other packages in terms of execution time and quality.
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The HHpred interactive server for protein homology detection and structure prediction
TL;DR: HHpred is a fast server for remote protein homology detection and structure prediction and is the first to implement pairwise comparison of profile hidden Markov models (HMMs) and allows to search a wide choice of databases.
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Protein homology detection by HMM--HMM comparison
TL;DR: A method for detecting distant homologous relationships between proteins based on the generalized alignment of protein sequences with a profile hidden Markov model (HMM) to the case of pairwise alignment of profile HMMs is presented.
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HHblits: lightning-fast iterative protein sequence searching by HMM-HMM alignment
TL;DR: An open-source, general-purpose tool that represents both query and database sequences by profile hidden Markov models (HMMs): 'HMM-HMM–based lightning-fast iterative sequence search' (HHblits; http://toolkit.genzentrum.lmu.de/hhblits/).
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A Completely Reimplemented MPI Bioinformatics Toolkit with a New HHpred Server at its Core
Lukas Zimmermann,Andrew Stephens,Seung-Zin Nam,David Rau,Jonas M. Kübler,Marko Lozajic,Felix Gabler,Johannes Söding,Andrei N. Lupas,Vikram Alva +9 more
TL;DR: The new version of the MPI Bioinformatics Toolkit is introduced, focusing on improved features for the comprehensive analysis of proteins, as well as on promoting teaching.