Torsten Schwede

54.8k citations
108 papers · 38.8k · 16 hit papers · h-index 53

Impact in

    • Protein Structure and Dynamics
    • RNA and protein synthesis mechanisms
    • Machine Learning in Bioinformatics
    • Microbial Metabolic Engineering and Bioproduction
  • Biotechnology top 0.05%
    • Enzyme Production and Characterization

Papers in

    • Protein Structure and Dynamics 64
    • RNA and protein synthesis mechanisms 20
    • Microbial Metabolic Engineering and Bioproduction 18
    • Bioinformatics and Genomic Networks 12
    • Genomics and Phylogenetic Studies 11
    • Genetics, Bioinformatics, and Biomedical Research 8
    • Enzyme Structure and Function 50

Torsten Schwede

105 papers receiving 38.3k citations

Torsten Schwede's Hit Papers

ProMod3—A versatile homology modelling toolbox 2021 · 186 citations
1860+7+14Years since publication2.5k5.0k7.5k

Peers

Torsten Schwede
Comparison fields: 5 of 182
  • Molecular Biology 25.7k
  • Biotechnology 2.5k
  • Computational Theory and Mathematics 2.7k
  • Infectious Diseases 2.9k
  • Molecular Medicine 717
Replace Roman A. Laskowski with:
Roman A. Laskowski United Kingdom
Thomas D. Goddard United States
Eric F. Pettersen United States
Yang Zhang China
Elaine C. Meng United States
Conrad C. Huang United States
Gregory S. Couch United States
Alex Bateman United Kingdom
Warren L. DeLano United States
Andrej Săli United States
Torsten Schwede relative to Roman A. Laskowski United Kingdom Roman A. Laskowski's profile →
Citations per field
00.5×1.7×
Roman A. Laskowski · 1×
Citations per year

Countries citing papers authored by Torsten Schwede

Since Specialization
Citations

This map shows the geographic impact of Torsten Schwede'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 Torsten Schwede with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Torsten Schwede more than expected).

Fields of papers citing papers by Torsten Schwede

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Torsten Schwede. 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 Torsten Schwede. The network helps show where Torsten Schwede may publish in the future.

Co-authors

The 25 scholars most cited alongside Torsten Schwede, 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 Torsten Schwede Line = papers co-authored together Torsten Schwede links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 108 papers — load more, or switch the sort, to bring in the rest.

#Work
1
SWISS-MODEL: homology modelling of protein structures and complexes
Hit paper breakdown →
20188674
2
The SWISS-MODEL workspace: a web-based environment for protein structure homology modelling
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20056013
3
SWISS-MODEL: an automated protein homology-modeling server
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20034622
4
SWISS-MODEL: modelling protein tertiary and quaternary structure using evolutionary information
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20143800
5
Toward the estimation of the absolute quality of individual protein structure models
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20101735
6
The SWISS-MODEL Repository and associated resources
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20081661
7
Automated comparative protein structure modeling with SWISS‐MODEL and Swiss‐PdbViewer: A historical perspective
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20091596
8
The SWISS-MODEL Repository—new features and functionality
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20161189
9
Protein structure homology modeling using SWISS-MODEL workspace
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20081025
10
lDDT: a local superposition-free score for comparing protein structures and models using distance difference tests
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2013674
11
QMEAN server for protein model quality estimation
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2009664
12
QMEANDisCo—distance constraints applied on model quality estimation
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2019643
13
Modeling protein quaternary structure of homo- and hetero-oligomers beyond binary interactions by homology
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2017584
14 2013421
15
Critical assessment of methods of protein structure prediction (CASP)—Round XIII
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2019330
16
Critical assessment of methods of protein structure prediction (CASP)—Round XIV
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2021291
17 2009240
18 2017230
19 2013201
20
ProMod3—A versatile homology modelling toolbox
Hit paper breakdown →
2021186

About Torsten Schwede

Torsten Schwede is a scholar working on Molecular Biology, Materials Chemistry, Computational Theory and Mathematics, Genetics and Sensory Systems, having authored 108 papers that have together received 38.8k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (64 papers), Enzyme Structure and Function (50 papers), RNA and protein synthesis mechanisms (20 papers), Microbial Metabolic Engineering and Bioproduction (18 papers), Computational Drug Discovery Methods (15 papers), Bioinformatics and Genomic Networks (12 papers), Genomics and Phylogenetic Studies (11 papers) and Genetics, Bioinformatics, and Biomedical Research (8 papers). The work is most often cited by research in Molecular Biology (25.7k citations), Biotechnology (2.5k citations), Computational Theory and Mathematics (2.7k citations), Infectious Diseases (2.9k citations) and Molecular Medicine (717 citations). Torsten Schwede has collaborated with scholars based in Switzerland, United States and Germany. Frequent co-authors include Lorenza Bordoli, Konstantin Arnold, Jürgen Kopp, Gabriel Studer, Andrew Waterhouse, Stefan Bienert, Marco Biasini, Martino Bertoni, Florian Kiefer and Pascal Benkert. Their work appears in journals such as Proteins Structure Function and Bioinformatics, Bioinformatics, Nucleic Acids Research, Journal of Biological Chemistry and Journal of Structural and Functional Genomics.

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.

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