Gopichand Gutti
- Pharmacology top 5%
- Cholinesterase and Neurodegenerative Diseases 15
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- Computational Drug Discovery Methods 15
- Toxicology top 5%
- Bioactive Compounds and Antitumor Agents 2
- Organic Chemistry top 10%
- Synthesis and biological activity 3
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- Medicinal Plants and Neuroprotection 2
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- Alzheimer's disease research and treatments 6
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- SARS-CoV-2 and COVID-19 Research 2
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- Estrogen and related hormone effects 2
- Co-authors
- Sushil Kumar SinghAshok KumarAnkit GaneshpurkarRayala SwethaDevendra KumarSairam KrishnamurthySukesh Kumar GuptaGyan Modi
- Journals
- European Journal of Medicinal Chemistry (4 papers)Future Medicinal Chemistry (4 papers)Bioorganic Chemistry (3 papers)
- Partner nations
- IndiaUnited StatesGermany
In The Last Decade
Gopichand Gutti
24 papers receiving 584 citations
Peers
Comparison fields: 5 of 81
- Pharmacology 238
- Computational Theory and Mathematics 217
- Toxicology 41
- Organic Chemistry 183
- Complementary and alternative medicine 50
Countries citing papers authored by Gopichand Gutti
This map shows the geographic impact of Gopichand Gutti'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 Gopichand Gutti with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gopichand Gutti more than expected).
Fields of papers citing papers by Gopichand Gutti
This network shows the impact of papers produced by Gopichand Gutti. 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 Gopichand Gutti. The network helps show where Gopichand Gutti may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Gopichand Gutti, 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 | 2024 | 4 | |
| 2 | 2024 | 9 | |
| 3 | 2023 | 22 | |
| 4 | 2023 | 6 | |
| 5 | 2022 | 5 | |
| 6 | 2022 | 5 | |
| 7 | 2021 | 11 | |
| 8 | 2021 | 26 | |
| 9 | 2021 | 7 | |
| 10 | 2021 | 6 | |
| 11 | 2019 | 10 | |
| 12 | 2019 | 12 | |
| 13 | 2019 | 34 | |
| 14 | 2019 | 46 | |
| 15 | 2019 | 23 | |
| 16 | 2019 | 25 | |
| 17 | 2019 | 98 | |
| 18 | 2019 | 38 | |
| 19 | 2018 | 72 | |
| 20 | 2018 | 18 |
About Gopichand Gutti
Gopichand Gutti is a scholar working on Computational Theory and Mathematics, Pharmacology, Toxicology, Complementary and alternative medicine and Physiology, having authored 24 papers that have together received 593 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (15 papers), Cholinesterase and Neurodegenerative Diseases (15 papers), Alzheimer's disease research and treatments (6 papers), Synthesis and biological activity (3 papers), Bioactive Compounds and Antitumor Agents (2 papers), SARS-CoV-2 and COVID-19 Research (2 papers), Medicinal Plants and Neuroprotection (2 papers) and Estrogen and related hormone effects (2 papers). The work is most often cited by research in Pharmacology (238 citations), Computational Theory and Mathematics (217 citations), Toxicology (41 citations), Organic Chemistry (183 citations) and Complementary and alternative medicine (50 citations). Gopichand Gutti has collaborated with scholars based in India, United States and Germany. Frequent co-authors include Sushil Kumar Singh, Ashok Kumar, Ankit Ganeshpurkar, Rayala Swetha, Devendra Kumar, Sairam Krishnamurthy, Devendra Kumar, Sukesh Kumar Gupta, Sairam Krishnamurthy and Gyan Modi. Their work appears in journals such as European Journal of Medicinal Chemistry, Future Medicinal Chemistry, Bioorganic Chemistry, Journal of Biomolecular Structure and Dynamics and Mini-Reviews in Medicinal Chemistry.
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.