Dilip Narayanan
Impact in
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- Computational Drug Discovery Methods
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- Genomics, phytochemicals, and oxidative stress
- Redox biology and oxidative stress
- Chemical Synthesis and Analysis
- Protein Degradation and Inhibitors
Papers in
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- Computational Drug Discovery Methods 6
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- Genomics, phytochemicals, and oxidative stress 5
- Redox biology and oxidative stress 3
- Protein Kinase Regulation and GTPase Signaling 1
- Protein Structure and Dynamics 1
- Co-authors
- Anders Bach (7 shared papers)Sara M. Ø. Solbak (5 shared papers)Kim T. Tran (4 shared papers)Dennis Özcelik (1 shared paper)Jie Zang (3 shared papers)Anthony D. Garcia (2 shared papers)Michael Gajhede (5 shared papers)Alejandro Aguayo‐Orozco (1 shared paper)
- Journals
- Journal of Medicinal Chemistry (6 papers)Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics (1 paper)Journal of Cheminformatics (1 paper)Protein Science (1 paper)Cancers (1 paper)
- Partner nations
- DenmarkUnited StatesNorway
In The Last Decade
Dilip Narayanan
13 papers receiving 305 citations
Peers
Comparison fields: 5 of 58
- Computational Theory and Mathematics 58
- Molecular Biology 205
- Toxicology 5
- Immunology 18
- Neurology 7
Countries citing papers authored by Dilip Narayanan
This map shows the geographic impact of Dilip Narayanan'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 Dilip Narayanan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dilip Narayanan more than expected).
Fields of papers citing papers by Dilip Narayanan
This network shows the impact of papers produced by Dilip Narayanan. 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 Dilip Narayanan. The network helps show where Dilip Narayanan may publish in the future.
Co-authors
The 25 scholars most cited alongside Dilip Narayanan, 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 | 2019 | 87 | |
| 2 | 2021 | 52 | |
| 3 | 2020 | 38 | |
| 4 | 2022 | 36 | |
| 5 | 2020 | 30 | |
| 6 | 2023 | 24 | |
| 7 | 2015 | 11 | |
| 8 | 2024 | 11 | |
| 9 | 2013 | 8 | |
| 10 | 2023 | 8 | |
| 11 | 2017 | 5 | |
| 12 | 2024 | 4 | |
| 13 | 2025 | 3 |
About Dilip Narayanan
Dilip Narayanan is a scholar working on Computational Theory and Mathematics, Molecular Biology, Immunology, Cancer Research and Rheumatology, having authored 13 papers that have together received 317 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (6 papers), Genomics, phytochemicals, and oxidative stress (5 papers), Redox biology and oxidative stress (3 papers), Neutrophil, Myeloperoxidase and Oxidative Mechanisms (2 papers), Protein Kinase Regulation and GTPase Signaling (1 paper), Protein Structure and Dynamics (1 paper), NF-κB Signaling Pathways (1 paper) and Cytokine Signaling Pathways and Interactions (1 paper). The work is most often cited by research in Computational Theory and Mathematics (58 citations), Molecular Biology (205 citations), Toxicology (5 citations), Immunology (18 citations) and Neurology (7 citations). Dilip Narayanan has collaborated with scholars based in Denmark, United States and Norway. Frequent co-authors include Anders Bach, Sara M. Ø. Solbak, Kim T. Tran, Dennis Özcelik, Jie Zang, Anthony D. Garcia, Michael Gajhede, Alejandro Aguayo‐Orozco, Michael Sattler and Roberta Brambilla. Their work appears in journals such as Journal of Medicinal Chemistry, Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics, Journal of Cheminformatics, Protein Science and Cancers.
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.