Srikanth Jupudi
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- Computational Drug Discovery Methods 21
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- Synthesis and biological activity 11
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- Cancer therapeutics and mechanisms 5
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- SARS-CoV-2 and COVID-19 Research 4
- Antimicrobial Resistance in Staphylococcus 3
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- Peptidase Inhibition and Analysis 4
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- Monoclonal and Polyclonal Antibodies Research 4
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- Bacterial Genetics and Biotechnology 4
- Co-authors
- Mohammed Afzal AzamKalirajan RajagopalGowramma ByranVadivelan RamachandranVeera Venkata Satyanarayana Reddy KarriBharat Kumar Reddy SanapalliDilep Kumar SigalapalliS.P. Dhanabal
- Journals
- SHILAP Revista de lepidopterología (1 paper)Scientific Reports (1 paper)Biochemical Journal (1 paper)
- Partner nations
- IndiaBangladeshSaudi Arabia
In The Last Decade
Srikanth Jupudi
45 papers receiving 336 citations
Peers
Comparison fields: 5 of 83
- Computational Theory and Mathematics 108
- Pharmacology 37
- Toxicology 14
- Complementary and alternative medicine 28
- Organic Chemistry 82
Countries citing papers authored by Srikanth Jupudi
This map shows the geographic impact of Srikanth Jupudi'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 Srikanth Jupudi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Srikanth Jupudi more than expected).
Fields of papers citing papers by Srikanth Jupudi
This network shows the impact of papers produced by Srikanth Jupudi. 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 Srikanth Jupudi. The network helps show where Srikanth Jupudi may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Srikanth Jupudi, 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 | 2025 | 1 | |
| 2 | 2025 | 2 | |
| 3 | 2024 | 2 | |
| 4 | 2024 | 5 | |
| 5 | 2023 | 2 | |
| 6 | 2023 | 3 | |
| 7 | 2023 | 3 | |
| 8 | 2023 | 5 | |
| 9 | 2023 | 3 | |
| 10 | 2022 | 1 | |
| 11 | 2022 | 2 | |
| 12 | 2021 | 14 | |
| 13 | 2021 | 0 | |
| 14 | 2021 | 14 | |
| 15 | 2021 | 12 | |
| 16 | 2020 | 50 | |
| 17 | 2019 | 22 | |
| 18 | 2019 | 8 | |
| 19 | 2019 | 6 | |
| 20 | SYNTHESIS OF 9-BROMO-N-SUBSTITUTED- 6H- INDOLO [2, 3-b] QUINOXALINE-3-SULFONAMIDE DERIVATIVES CONTAINING QUINOXALINE MOIETY AS PROSPECTIVE ANTIMICROBIAL AGENTS | 2013 | 1 |
About Srikanth Jupudi
Srikanth Jupudi is a scholar working on Computational Theory and Mathematics, Molecular Medicine and Toxicology, having authored 48 papers that have together received 343 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (21 papers), Synthesis and biological activity (11 papers), Cancer therapeutics and mechanisms (5 papers), SARS-CoV-2 and COVID-19 Research (4 papers), Peptidase Inhibition and Analysis (4 papers), Monoclonal and Polyclonal Antibodies Research (4 papers), Bacterial Genetics and Biotechnology (4 papers) and Antimicrobial Resistance in Staphylococcus (3 papers). The work is most often cited by research in Computational Theory and Mathematics (108 citations), Pharmacology (37 citations) and Toxicology (14 citations). Srikanth Jupudi has collaborated with scholars based in India, Bangladesh and Saudi Arabia. Frequent co-authors include Mohammed Afzal Azam, Kalirajan Rajagopal, Gowramma Byran, Vadivelan Ramachandran, Veera Venkata Satyanarayana Reddy Karri, Bharat Kumar Reddy Sanapalli, Dilep Kumar Sigalapalli, S.P. Dhanabal, Ashish Wadhwani and Antony Justin. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Reports and Biochemical Journal.
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.