Gabriel Studer
- Molecular Biology top 0.5%
- Protein Structure and Dynamics 18
- RNA and protein synthesis mechanisms 7
- Microbial Metabolic Engineering and Bioproduction 5
- Bioinformatics and Genomic Networks 3
- Machine Learning in Bioinformatics 2
- Biotechnology top 0.2%
- Infectious Diseases top 1%
- Molecular Medicine top 1%
- Computational Theory and Mathematics top 0.5%
- Computational Drug Discovery Methods 5
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- Enzyme Structure and Function 7
- Machine Learning in Materials Science 2
- Co-authors
- Torsten SchwedeAndrew WaterhouseStefan BienertLorenza BordoliMartino BertoniGerardo TaurielloTjaart de BeerRafal Gumienny
- Journals
- Proteins Structure Function and Bioinformatics (8 papers)Nucleic Acids Research (4 papers)Bioinformatics (3 papers)
- Partner nations
- SwitzerlandUnited KingdomUnited States
In The Last Decade
Gabriel Studer
21 papers receiving 15.0k citations
Hit Papers
Peers
Comparison fields: 5 of 169
- Molecular Biology 9.5k
- Biotechnology 985
- Infectious Diseases 1.5k
- Molecular Medicine 328
- Computational Theory and Mathematics 977
Countries citing papers authored by Gabriel Studer
This map shows the geographic impact of Gabriel Studer'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 Gabriel Studer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gabriel Studer more than expected).
Fields of papers citing papers by Gabriel Studer
This network shows the impact of papers produced by Gabriel Studer. 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 Gabriel Studer. The network helps show where Gabriel Studer may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Gabriel Studer, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 2 | |
| 3 | 2024 | 42 | |
| 4 | 2024 | 3 | |
| 5 | 2023 | 37 | |
| 6 | 2023 | 22 | |
| 7 | 2023 | 20 | |
| 8 | 2023 | 25 | |
| 9 | 2023 | 78 | |
| 10 | ProMod3—A versatile homology modelling toolboxbreakdown → | 2021 | 186 |
| 11 | 2020 | 25 | |
| 12 | QMEANDisCo—distance constraints applied on model quality estimationbreakdown → | 2019 | 643 |
| 13 | 2019 | 58 | |
| 14 | 2019 | 29 | |
| 15 | 2018 | 13 | |
| 16 | SWISS-MODEL: homology modelling of protein structures and complexesbreakdown → | 2018 | 8674 |
| 17 | The SWISS-MODEL Repository—new features and functionalitybreakdown → | 2016 | 1189 |
| 18 | SWISS-MODEL: modelling protein tertiary and quaternary structure using evolutionary informationbreakdown → | 2014 | 3800 |
| 19 | 2014 | 117 | |
| 20 | 2013 | 109 |
About Gabriel Studer
Gabriel Studer is a scholar working on Computational Theory and Mathematics, Molecular Biology and Software, having authored 22 papers that have together received 15.2k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (18 papers), RNA and protein synthesis mechanisms (7 papers), Enzyme Structure and Function (7 papers), Computational Drug Discovery Methods (5 papers), Microbial Metabolic Engineering and Bioproduction (5 papers), Bioinformatics and Genomic Networks (3 papers), Machine Learning in Bioinformatics (2 papers) and Machine Learning in Materials Science (2 papers). The work is most often cited by research in Molecular Biology (9.5k citations), Biotechnology (985 citations) and Infectious Diseases (1.5k citations). Gabriel Studer has collaborated with scholars based in Switzerland, United Kingdom and United States. Frequent co-authors include Torsten Schwede, Andrew Waterhouse, Stefan Bienert, Lorenza Bordoli, Martino Bertoni, Gerardo Tauriello, Tjaart de Beer, Rafal Gumienny, Christine Rempfer and Rosalba Lepore. Their work appears in journals such as Proteins Structure Function and Bioinformatics, Nucleic Acids Research, Bioinformatics, PLoS Computational Biology and International Journal of Molecular Sciences.
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.