Vaibhav Tiwari
- Cell Biology top 2%
- Proteoglycans and glycosaminoglycans research 23
- Epidemiology top 2%
- Herpesvirus Infections and Treatments 46
- Cytomegalovirus and herpesvirus research 12
- Immunology top 5%
- interferon and immune responses 5
- Virology top 5%
- Parasitology top 5%
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- Glycosylation and Glycoproteins Research 12
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- Virus-based gene therapy research 10
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- Systemic Lupus Erythematosus Research 10
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- SARS-CoV-2 and COVID-19 Research 6
- Co-authors
- Deepak ShuklaTibor Vályi-NagyChristian ClémentJianbo YueP.M. ScanlanJian LiuYogendra Kumar MishraRainer Adelung
- Cited by
- Cell BiologyEpidemiologyImmunology
- Journals
- Journal of Biological Chemistry (2 papers)The Journal of Experimental Medicine (1 paper)SHILAP Revista de lepidopterología (1 paper)
- Partner nations
- United StatesIndiaUnited Kingdom
In The Last Decade
Vaibhav Tiwari
80 papers receiving 3.0k citations
Peers
Comparison fields: 5 of 130
- Cell Biology 752
- Epidemiology 1.3k
- Immunology 582
- Virology 109
- Parasitology 130
Countries citing papers authored by Vaibhav Tiwari
This map shows the geographic impact of Vaibhav Tiwari'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 Vaibhav Tiwari with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vaibhav Tiwari more than expected).
Fields of papers citing papers by Vaibhav Tiwari
This network shows the impact of papers produced by Vaibhav Tiwari. 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 Vaibhav Tiwari. The network helps show where Vaibhav Tiwari may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Vaibhav Tiwari, 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 | 2023 | 2 | |
| 2 | 2022 | 3 | |
| 3 | 2022 | 16 | |
| 4 | 2016 | 2 | |
| 5 | 2015 | 41 | |
| 6 | 2014 | 12 | |
| 7 | 2013 | 31 | |
| 8 | 2012 | 34 | |
| 9 | 2012 | 50 | |
| 10 | 2011 | 93 | |
| 11 | 2010 | 21 | |
| 12 | 2008 | 115 | |
| 13 | 2007 | 37 | |
| 14 | 2007 | 23 | |
| 15 | 2007 | 50 | |
| 16 | 2006 | 108 | |
| 17 | 2004 | 38 | |
| 18 | Suitability of liquid cultures for in vitro multiplication of Bacopa Monniera (L.) Wettst. | 2000 | 16 |
| 19 | 1998 | 72 | |
| 20 | A new technique for the propagation of somatic wheat embryos | 1997 | 1 |
About Vaibhav Tiwari
Vaibhav Tiwari is a scholar working on Cell Biology, Epidemiology and Immunology, having authored 80 papers that have together received 3.1k indexed citations. Recurring topics across this work include Herpesvirus Infections and Treatments (46 papers), Proteoglycans and glycosaminoglycans research (23 papers), Glycosylation and Glycoproteins Research (12 papers), Cytomegalovirus and herpesvirus research (12 papers), Virus-based gene therapy research (10 papers), Systemic Lupus Erythematosus Research (10 papers), SARS-CoV-2 and COVID-19 Research (6 papers) and interferon and immune responses (5 papers). The work is most often cited by research in Cell Biology (752 citations), Epidemiology (1.3k citations) and Immunology (582 citations). Vaibhav Tiwari has collaborated with scholars based in United States, India and United Kingdom. Frequent co-authors include Deepak Shukla, Tibor Vályi-Nagy, Christian Clément, Jianbo Yue, P.M. Scanlan, Jian Liu, Yogendra Kumar Mishra, Rainer Adelung, Umesh R. Desai and Thessicar E. Antoine. Their work appears in journals such as Journal of Biological Chemistry, The Journal of Experimental Medicine and SHILAP Revista de lepidopterología.
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.