Upendra N. Dwivedi
- Plant Science top 1%
- Molecular Biology top 5%
- Biotechnology top 1%
- Biochemistry top 2%
- Food Science top 5%
- Co-authors
- Veda P. PandeyManika AwasthiRupinder SinghPriyanka SinghAnoop KumarSmita RastogiSwati SinghPoonam Kakkar
- Topics
- Enzyme-mediated dye degradation (15 papers)Computational Drug Discovery Methods (13 papers)Plant Gene Expression Analysis (11 papers)
- Partner nations
- IndiaUnited StatesUnited Kingdom
In The Last Decade
Upendra N. Dwivedi
112 papers receiving 3.6k citations
Hit Papers
Peers
Comparison fields: 5 of 142
- Plant Science 2.1k
- Molecular Biology 1.4k
- Biotechnology 446
- Biochemistry 263
- Food Science 261
Countries citing papers authored by Upendra N. Dwivedi
This map shows the geographic impact of Upendra N. Dwivedi'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 Upendra N. Dwivedi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Upendra N. Dwivedi more than expected).
Fields of papers citing papers by Upendra N. Dwivedi
This network shows the impact of papers produced by Upendra N. Dwivedi. 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 Upendra N. Dwivedi. The network helps show where Upendra N. Dwivedi may publish in the future.
Co-authorship network of co-authors of Upendra N. Dwivedi
This figure shows the co-authorship network connecting the top 25 collaborators of Upendra N. Dwivedi. A scholar is included among the top collaborators of Upendra N. Dwivedi 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 Upendra N. Dwivedi. Upendra N. Dwivedi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 52 | |
| 3 | 39 | |
| 4 | 9 | |
| 5 | 4 | |
| 6 | Anti-Angiogenic Potential of Secondary Metabolites against Tyrosine Kinase Domain of Vascular Endothelial Growth Factor Receptor-1: An in silicoApproach | 1 |
| 7 | Studies on correlation and path coefficient analysis for yield and yield related traits in Indian mustard (Brassica juncea L. Czern & Coss.) under timely and late sown conditions | 6 |
| 8 | Fenugreek (Trigonella foenum-graecum L.) A potential source of dietary fibres and steroidal sapogenin (Diosgenin) | 3 |
| 9 | 73 | |
| 10 | 80 | |
| 11 | 17 | |
| 12 | 2 | |
| 13 | 45 | |
| 14 | 7 | |
| 15 | 35 | |
| 16 | 186 | |
| 17 | 31 | |
| 18 | 38 | |
| 19 | 35 | |
| 20 | 4 |
About Upendra N. Dwivedi
Upendra N. Dwivedi is a scholar working on Plant Science, Complementary and alternative medicine and Horticulture, having authored 115 papers that have together received 3.8k indexed citations. Recurring topics across this work include Enzyme-mediated dye degradation (15 papers), Computational Drug Discovery Methods (13 papers) and Plant Gene Expression Analysis (11 papers). The work is most often cited by research in Plant Science (2.1k citations), Biotechnology (446 citations) and Biochemistry (263 citations). Upendra N. Dwivedi has collaborated with scholars based in India, United States and United Kingdom. Frequent co-authors include Veda P. Pandey, Manika Awasthi, Rupinder Singh, Priyanka Singh, Anoop Kumar, Smita Rastogi, Swati Singh, Poonam Kakkar, Nivedita Jaiswal and Sameeksha Tiwari. Their work appears in journals such as Journal of Biological Chemistry, PLoS ONE and Journal of Molecular Biology.
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.