Justas Dauparas
About
In The Last Decade
Justas Dauparas
19 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 108
- Molecular Biology 945
- Materials Chemistry 193
- Biomedical Engineering 122
- Computational Theory and Mathematics 95
- Radiology, Nuclear Medicine and Imaging 87
Countries citing papers authored by Justas Dauparas
This map shows the geographic impact of Justas Dauparas'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 Justas Dauparas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Justas Dauparas more than expected).
Fields of papers citing papers by Justas Dauparas
This network shows the impact of papers produced by Justas Dauparas. 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 Justas Dauparas. The network helps show where Justas Dauparas may publish in the future.
Co-authorship network of co-authors of Justas Dauparas
This figure shows the co-authorship network connecting the top 25 collaborators of Justas Dauparas. A scholar is included among the top collaborators of Justas Dauparas 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 Justas Dauparas. Justas Dauparas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | Atomic context-conditioned protein sequence design using LigandMPNN breakdown → | 39 |
| 3 | 0 | |
| 4 | 16 | |
| 5 | Computational design of soluble and functional membrane protein analogues breakdown → | 40 |
| 6 | Improving Protein Expression, Stability, and Function with ProteinMPNN breakdown → | 121 |
| 7 | 6 | |
| 8 | Improving de novo protein binder design with deep learning breakdown → | 158 |
| 9 | Peptide-binding specificity prediction using fine-tuned protein structure prediction networks breakdown → | 63 |
| 10 | Mega-scale experimental analysis of protein folding stability in biology and design breakdown → | 139 |
| 11 | De novo design of luciferases using deep learning breakdown → | 241 |
| 12 | 4 | |
| 13 | 21 | |
| 14 | Hallucinating symmetric protein assemblies breakdown → | 113 |
| 15 | 3 | |
| 16 | 15 | |
| 17 | Improved protein structure refinement guided by deep learning based accuracy estimation breakdown → | 157 |
| 18 | 2 | |
| 19 | 35 | |
| 20 | 32 |
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.