Kieran Didi
Impact in
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- Computational Drug Discovery Methods
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- Monoclonal and Polyclonal Antibodies Research
Papers in
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- Glycosylation and Glycoproteins Research 2
- Protein Structure and Dynamics 2
- Genomics and Phylogenetic Studies 2
- Ubiquitin and proteasome pathways 1
- Protein Degradation and Inhibitors 1
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- Computational Drug Discovery Methods 2
- Co-authors
- Píetro Lió (2 shared papers)Ilia Igashov (1 shared paper)Michael M. Bronstein (1 shared paper)Bruno E. Correia (1 shared paper)Tom L. Blundell (1 shared paper)Max Welling (1 shared paper)Weitao Du (1 shared paper)Arne Schneuing (1 shared paper)
- Journals
- Nature Computational Science (2 papers)Nature Methods (1 paper)Frontiers in Bioengineering and Biotechnology (1 paper)Nature Communications (1 paper)Nature Machine Intelligence (1 paper)
- Partner nations
- United KingdomGermanyUnited States
In The Last Decade
Kieran Didi
6 papers receiving 228 citations
Kieran Didi's Hit Papers
Peers
Comparison fields: 5 of 57
- Computational Theory and Mathematics 45
- Radiology, Nuclear Medicine and Imaging 43
- Molecular Biology 126
- Structural Biology 1
- Materials Chemistry 28
Countries citing papers authored by Kieran Didi
This map shows the geographic impact of Kieran Didi'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 Kieran Didi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kieran Didi more than expected).
Fields of papers citing papers by Kieran Didi
This network shows the impact of papers produced by Kieran Didi. 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 Kieran Didi. The network helps show where Kieran Didi may publish in the future.
Co-authors
The 25 scholars most cited alongside Kieran Didi, 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 | Structure-based drug design with equivariant diffusion models Hit paper breakdown → | 2024 | 79 |
| 2 | 2022 | 60 | |
| 3 | 2024 | 47 | |
| 4 | 2024 | 36 | |
| 5 | 2025 | 8 | |
| 6 | 2025 | 1 | |
| 7 | 2024 | 0 | |
| 8 | 2026 | 0 |
About Kieran Didi
Kieran Didi is a scholar working on Molecular Biology, Computational Theory and Mathematics, Radiology, Nuclear Medicine and Imaging, Ecology and Hematology, having authored 8 papers that have together received 231 indexed citations. Recurring topics across this work include Glycosylation and Glycoproteins Research (2 papers), Protein Structure and Dynamics (2 papers), Genomics and Phylogenetic Studies (2 papers), Computational Drug Discovery Methods (2 papers), Monoclonal and Polyclonal Antibodies Research (2 papers), Ubiquitin and proteasome pathways (1 paper), Protein Degradation and Inhibitors (1 paper) and Multiple Myeloma Research and Treatments (1 paper). The work is most often cited by research in Computational Theory and Mathematics (45 citations), Radiology, Nuclear Medicine and Imaging (43 citations), Molecular Biology (126 citations), Structural Biology (1 citation) and Materials Chemistry (28 citations). Kieran Didi has collaborated with scholars based in United Kingdom, Germany and United States. Frequent co-authors include Píetro Lió, Ilia Igashov, Michael M. Bronstein, Bruno E. Correia, Tom L. Blundell, Max Welling, Weitao Du, Arne Schneuing, Carla P. Gomes and Yuanqi Du. Their work appears in journals such as Nature Computational Science, Nature Methods, Frontiers in Bioengineering and Biotechnology, Nature Communications and Nature Machine Intelligence.
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.