Inna Goreshnik
- Molecular Biology top 10%
- Infectious Diseases top 5%
- Radiology, Nuclear Medicine and Imaging top 10%
- Materials Chemistry
- Computational Theory and Mathematics top 5%
- Co-authors
- David BakerLauren CarterLance StewartBrian CoventryRita E. ChenL. M. MillerLongxing CaoMichael Diamond
- Topics
- RNA and protein synthesis mechanisms (5 papers)Protein Structure and Dynamics (3 papers)Monoclonal and Polyclonal Antibodies Research (3 papers)
- Journals
- ScienceProceedings of the National Academy of SciencesJournal of the American Chemical Society
- Partner nations
- United StatesDenmarkCanada
In The Last Decade
Inna Goreshnik
13 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 87
- Molecular Biology 827
- Infectious Diseases 301
- Radiology, Nuclear Medicine and Imaging 177
- Materials Chemistry 134
- Computational Theory and Mathematics 130
Countries citing papers authored by Inna Goreshnik
This map shows the geographic impact of Inna Goreshnik'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 Inna Goreshnik with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Inna Goreshnik more than expected).
Fields of papers citing papers by Inna Goreshnik
This network shows the impact of papers produced by Inna Goreshnik. 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 Inna Goreshnik. The network helps show where Inna Goreshnik may publish in the future.
Co-authorship network of co-authors of Inna Goreshnik
This figure shows the co-authorship network connecting the top 25 collaborators of Inna Goreshnik. A scholar is included among the top collaborators of Inna Goreshnik based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Inna Goreshnik. Inna Goreshnik is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 19 | |
| 4 | Improving de novo protein binder design with deep learningbreakdown → | 158 |
| 5 | 26 | |
| 6 | 40 | |
| 7 | 46 | |
| 8 | 53 | |
| 9 | De novo design of picomolar SARS-CoV-2 miniprotein inhibitorsbreakdown → | 451 |
| 10 | 1 | |
| 11 | Global analysis of protein folding using massively parallel design, synthesis, and testingbreakdown → | 305 |
| 12 | 16 | |
| 13 | 4 | |
| 14 | 22 |
About Inna Goreshnik
Inna Goreshnik is a scholar working on Biotechnology, Virology and Molecular Biology, having authored 14 papers that have together received 1.1k indexed citations. Recurring topics across this work include RNA and protein synthesis mechanisms (5 papers), Protein Structure and Dynamics (3 papers) and Monoclonal and Polyclonal Antibodies Research (3 papers). The work is most often cited by research in Infectious Diseases (301 citations), Molecular Biology (827 citations) and Computational Theory and Mathematics (130 citations). Inna Goreshnik has collaborated with scholars based in United States, Denmark and Canada. Frequent co-authors include David Baker, Lauren Carter, Lance Stewart, Brian Coventry, Rita E. Chen, L. M. Miller, Longxing Cao, Michael Diamond, James Brett Case and Eva‐Maria Strauch. Their work appears in journals such as Science, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.
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.