Johannes Söding

49k citations
121 papers · 36.2k · 12 hit papers · h-index 61

Impact in

    • Protein Structure and Dynamics
    • Genomics and Phylogenetic Studies
    • Machine Learning in Bioinformatics
    • Genomics and Chromatin Dynamics
    • RNA and protein synthesis mechanisms
  • Ecology top 0.2%
    • Bacteriophages and microbial interactions

Papers in

    • Protein Structure and Dynamics 33
    • Genomics and Phylogenetic Studies 32
    • Genomics and Chromatin Dynamics 19
    • RNA Research and Splicing 10
    • Machine Learning in Bioinformatics 10
    • RNA and protein synthesis mechanisms 5
    • Cold Atom Physics and Bose-Einstein Condensates 12
    • Quantum optics and atomic interactions 5

Johannes Söding

117 papers receiving 35.8k citations

Johannes Söding's Hit Papers

Fast and accurate protein structure search with Foldseek 2023 · 1.4k citations
1.4k0+7+14Years since publication4k8k12k

Peers

Johannes Söding
Comparison fields: 5 of 161
  • Molecular Biology 19.9k
  • Ecology 3.7k
  • Endocrinology 624
  • Genetics 3.6k
  • Biotechnology 668
Replace Liisa Holm with:
Liisa Holm Finland
Martin Steinegger South Korea
Andreas Wilm Singapore
Andrei N. Lupas Germany
Hamish McWilliam United Kingdom
Weizhong Li China
Kira S. Makarova United States
Erik L. L. Sonnhammer Sweden
ROBERT FINN United Kingdom
Thomas Madden United States
Johannes Söding relative to Liisa Holm Finland Liisa Holm's profile →
Citations per field
00.5×2×3×3.9×
Liisa Holm · 1×
Citations per year

Countries citing papers authored by Johannes Söding

Since Specialization
Citations

This map shows the geographic impact of Johannes Söding's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Johannes Söding with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Johannes Söding more than expected).

Fields of papers citing papers by Johannes Söding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Johannes Söding. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Johannes Söding. The network helps show where Johannes Söding may publish in the future.

Co-authors

The 25 scholars most cited alongside Johannes Söding, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Johannes Söding Line = papers co-authored together Johannes Söding links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 121 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Fast, scalable generation of high‐quality protein multiple sequence alignments using Clustal Omega
Hit paper breakdown →
201112158
2
The HHpred interactive server for protein homology detection and structure prediction
Hit paper breakdown →
20053020
3
MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets
Hit paper breakdown →
20172770
4
Protein homology detection by HMM–HMM comparison
Hit paper breakdown →
20042004
5
A Completely Reimplemented MPI Bioinformatics Toolkit with a New HHpred Server at its Core
Hit paper breakdown →
20171815
6
HHblits: lightning-fast iterative protein sequence searching by HMM-HMM alignment
Hit paper breakdown →
20111782
7
Fast and accurate protein structure search with Foldseek
Hit paper breakdown →
20231384
8
HH-suite3 for fast remote homology detection and deep protein annotation
Hit paper breakdown →
2019767
9
Clustering huge protein sequence sets in linear time
Hit paper breakdown →
2018584
10
Protein Sequence Analysis Using the MPI Bioinformatics Toolkit
Hit paper breakdown →
2020549
11
Uniclust databases of clustered and deeply annotated protein sequences and alignments
Hit paper breakdown →
2016518
12
MMseqs2 desktop and local web server app for fast, interactive sequence searches
Hit paper breakdown →
2019408
13 2009385
14 2010367
15 2016318
16 2019306
17 2014302
18 2006249
19 2019205
20 2003203

About Johannes Söding

Johannes Söding is a scholar working on Molecular Biology, Atomic and Molecular Physics, and Optics, Genetics, Astronomy and Astrophysics and Materials Chemistry, having authored 121 papers that have together received 36.2k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (33 papers), Genomics and Phylogenetic Studies (32 papers), Genomics and Chromatin Dynamics (19 papers), Cold Atom Physics and Bose-Einstein Condensates (12 papers), RNA Research and Splicing (10 papers), Machine Learning in Bioinformatics (10 papers), RNA and protein synthesis mechanisms (5 papers) and Quantum optics and atomic interactions (5 papers). The work is most often cited by research in Molecular Biology (19.9k citations), Ecology (3.7k citations), Endocrinology (624 citations), Genetics (3.6k citations) and Biotechnology (668 citations). Johannes Söding has collaborated with scholars based in Germany, South Korea and United States. Frequent co-authors include Martin Steinegger, A. Biegert, Andrei N. Lupas, Michael Remmert, Weizhong Li, Toby J. Gibson, Andreas Wilm, Desmond G. Higgins, Fabian Sievers and Kevin J. Karplus. Their work appears in journals such as Bioinformatics, Nucleic Acids Research, Molecular Cell, PLoS ONE and Nature Methods.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact