Kieran Didi
Impact in
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- Computational Drug Discovery Methods
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- RNA Research and Splicing
- Protein Structure and Dynamics
- RNA and protein synthesis mechanisms
- RNA modifications and cancer
- vaccines and immunoinformatics approaches
Papers in
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- Genomics and Phylogenetic Studies 2
- Protein Structure and Dynamics 2
- Glycosylation and Glycoproteins Research 2
- Machine Learning in Bioinformatics 1
- Protein Degradation and Inhibitors 1
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- Computational Drug Discovery Methods 2
- Co-authors
- Píetro Lió (2 shared papers)Bruno E. Correia (1 shared paper)Tom L. Blundell (1 shared paper)Max Welling (1 shared paper)Pietro Sormanni (1 shared paper)Matthew Greenig (1 shared paper)Michael M. Bronstein (1 shared paper)Stéfano Ricagno (1 shared paper)
- Journals
- Nature Computational Science (2 papers)Nature Methods (1 paper)Computational and Structural Biotechnology Journal (1 paper)Nature Communications (1 paper)Frontiers in Bioengineering and Biotechnology (1 paper)
- Partner nations
- United KingdomGermanyUnited States
In The Last Decade
Kieran Didi
5 papers receiving 169 citations
Kieran Didi's Hit Papers
Peers
Comparison fields: 5 of 57
- Computational Theory and Mathematics 39
- Molecular Biology 120
- Radiology, Nuclear Medicine and Imaging 40
- Structural Biology 1
- Biochemistry 4
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 | 2022 | 53 | |
| 2 | Structure-based drug design with equivariant diffusion models Hit paper breakdown → | 2024 | 52 |
| 3 | 2024 | 40 | |
| 4 | 2024 | 27 | |
| 5 | 2025 | 3 | |
| 6 | 2024 | 0 | |
| 7 | 2025 | 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 7 papers that have together received 175 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (2 papers), Genomics and Phylogenetic Studies (2 papers), Monoclonal and Polyclonal Antibodies Research (2 papers), Protein Structure and Dynamics (2 papers), Glycosylation and Glycoproteins Research (2 papers), Machine Learning in Bioinformatics (1 paper), Protein Degradation and Inhibitors (1 paper) and Bacteriophages and microbial interactions (1 paper). The work is most often cited by research in Computational Theory and Mathematics (39 citations), Molecular Biology (120 citations), Radiology, Nuclear Medicine and Imaging (40 citations), Structural Biology (1 citation) and Biochemistry (4 citations). Kieran Didi has collaborated with scholars based in United Kingdom, Germany and United States. Frequent co-authors include Píetro Lió, Bruno E. Correia, Tom L. Blundell, Max Welling, Pietro Sormanni, Matthew Greenig, Michael M. Bronstein, Stéfano Ricagno, Charles B. Harris and Cristina Visentin. Their work appears in journals such as Nature Computational Science, Nature Methods, Computational and Structural Biotechnology Journal, Nature Communications and Frontiers in Bioengineering and Biotechnology.
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.