Sandra Viknander
Impact in
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- Protein Structure and Dynamics
- RNA and protein synthesis mechanisms
- Machine Learning in Bioinformatics
- Microbial Metabolic Engineering and Bioproduction
- Enzyme Catalysis and Immobilization
- Genomics and Phylogenetic Studies
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- Computational Drug Discovery Methods
Papers in
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- Microbial Metabolic Engineering and Bioproduction 4
- Protein Structure and Dynamics 4
- Genomics and Phylogenetic Studies 1
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- Advanced Proteomics Techniques and Applications 2
- Co-authors
- Aleksej Zelezniak (7 shared papers)Martin K. M. Engqvist (2 shared papers)Jan Zrimec (3 shared papers)Elzbieta Rembeza (1 shared paper)Rolandas Meškys (1 shared paper)Vykintas Jauniškis (1 shared paper)Audrius Laurynėnas (1 shared paper)Simona Povilonienė (1 shared paper)
- Journals
- Protein Science (3 papers)Nature Machine Intelligence (1 paper)Nature Biotechnology (1 paper)Nucleic Acids Research (1 paper)Nature (1 paper)
- Partner nations
- LithuaniaSwedenUnited Kingdom
In The Last Decade
Sandra Viknander
8 papers receiving 292 citations
Sandra Viknander's Hit Papers
Peers
Comparison fields: 5 of 67
- Molecular Biology 237
- Computational Theory and Mathematics 33
- Microbiology 8
- Biophysics 6
- Biotechnology 7
Countries citing papers authored by Sandra Viknander
This map shows the geographic impact of Sandra Viknander'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 Sandra Viknander with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sandra Viknander more than expected).
Fields of papers citing papers by Sandra Viknander
This network shows the impact of papers produced by Sandra Viknander. 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 Sandra Viknander. The network helps show where Sandra Viknander may publish in the future.
Co-authors
The 25 scholars most cited alongside Sandra Viknander, 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 | Expanding functional protein sequence spaces using generative adversarial networks Hit paper breakdown → | 2021 | 221 |
| 2 | 2024 | 39 | |
| 3 | 2022 | 22 | |
| 4 | 2025 | 8 | |
| 5 | 2024 | 3 | |
| 6 | 2023 | 3 | |
| 7 | 2024 | 2 | |
| 8 | 2025 | 2 |
About Sandra Viknander
Sandra Viknander is a scholar working on Molecular Biology, Spectroscopy, Materials Chemistry, Computational Theory and Mathematics and Biotechnology, having authored 8 papers that have together received 300 indexed citations. Recurring topics across this work include Microbial Metabolic Engineering and Bioproduction (4 papers), Protein Structure and Dynamics (4 papers), Advanced Proteomics Techniques and Applications (2 papers), Genomics and Phylogenetic Studies (1 paper), Computational Drug Discovery Methods (1 paper), Enzyme Structure and Function (1 paper), Enzyme Production and Characterization (1 paper) and Machine Learning in Materials Science (1 paper). The work is most often cited by research in Molecular Biology (237 citations), Computational Theory and Mathematics (33 citations), Microbiology (8 citations), Biophysics (6 citations) and Biotechnology (7 citations). Sandra Viknander has collaborated with scholars based in Lithuania, Sweden and United Kingdom. Frequent co-authors include Aleksej Zelezniak, Martin K. M. Engqvist, Jan Zrimec, Elzbieta Rembeza, Rolandas Meškys, Vykintas Jauniškis, Audrius Laurynėnas, Simona Povilonienė, Otto Savolainen and Sean R. Johnson. Their work appears in journals such as Protein Science, Nature Machine Intelligence, Nature Biotechnology, Nucleic Acids Research and Nature.
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.