Varghese John
- Molecular Biology top 10%
- Physiology top 5%
- Pharmacology top 2%
- Computational Theory and Mathematics top 2%
- Cellular and Molecular Neuroscience top 10%
- Co-authors
- Dale E. BredesenOlivier DescampsRammohan V. RaoSukanto SinhaJesus CampagnaMichael J. BienkowskiTina BilousovaRobert L. Heinrikson
- Topics
- Alzheimer's disease research and treatments (24 papers)Cholinesterase and Neurodegenerative Diseases (16 papers)Computational Drug Discovery Methods (14 papers)
- Journals
- NatureProceedings of the National Academy of SciencesJournal of the American Chemical Society
- Partner nations
- United StatesJapanFrance
In The Last Decade
Varghese John
63 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 97
- Molecular Biology 706
- Physiology 651
- Pharmacology 407
- Computational Theory and Mathematics 338
- Cellular and Molecular Neuroscience 169
Countries citing papers authored by Varghese John
This map shows the geographic impact of Varghese John'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 Varghese John with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Varghese John more than expected).
Fields of papers citing papers by Varghese John
This network shows the impact of papers produced by Varghese John. 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 Varghese John. The network helps show where Varghese John may publish in the future.
Co-authorship network of co-authors of Varghese John
This figure shows the co-authorship network connecting the top 25 collaborators of Varghese John. A scholar is included among the top collaborators of Varghese John 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 Varghese John. Varghese John is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 3 | |
| 3 | 3 | |
| 4 | 0 | |
| 5 | 3 | |
| 6 | 4 | |
| 7 | 42 | |
| 8 | 20 | |
| 9 | 5 | |
| 10 | 3 | |
| 11 | 30 | |
| 12 | 7 | |
| 13 | 3 | |
| 14 | 34 | |
| 15 | 64 | |
| 16 | 12 | |
| 17 | 33 | |
| 18 | 46 | |
| 19 | 14 | |
| 20 | 24 |
About Varghese John
Varghese John is a scholar working on Pharmacology, Physiology and Pharmaceutical Science, having authored 66 papers that have together received 1.6k indexed citations. Recurring topics across this work include Alzheimer's disease research and treatments (24 papers), Cholinesterase and Neurodegenerative Diseases (16 papers) and Computational Drug Discovery Methods (14 papers). The work is most often cited by research in Physiology (651 citations), Pharmacology (407 citations) and Computational Theory and Mathematics (338 citations). Varghese John has collaborated with scholars based in United States, Japan and France. Frequent co-authors include Dale E. Bredesen, Olivier Descamps, Rammohan V. Rao, Sukanto Sinha, Jesus Campagna, Michael J. Bienkowski, Tina Bilousova, Robert L. Heinrikson, James P. Beck and Karen S. Poksay. Their work appears in journals such as Nature, 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.