Emilio Mateev
Impact in
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- Synthesis and Characterization of Pyrroles
- Synthesis and biological activity
- Multicomponent Synthesis of Heterocycles
- Synthesis and Biological Evaluation
- Click Chemistry and Applications
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- Computational Drug Discovery Methods
Papers in
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- Synthesis and biological activity 10
- Synthesis and Characterization of Pyrroles 7
- Multicomponent Synthesis of Heterocycles 6
- Free Radicals and Antioxidants 5
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- Computational Drug Discovery Methods 18
- Co-authors
- Alexander Zlatkov (25 shared papers)Magdalena Kondeva-Burdina (20 shared papers)Virginia Tzankova (6 shared papers)Maya Georgieva (14 shared papers)Iva Valkova (8 shared papers)Ali Irfan (14 shared papers)Shubham Sharma (6 shared papers)Vasco Azevedo (1 shared paper)
In The Last Decade
Emilio Mateev
33 papers receiving 276 citations
Peers
Comparison fields: 5 of 59
- Organic Chemistry 134
- Computational Theory and Mathematics 65
- Pharmacology 57
- Pharmacology 15
- Toxicology 5
Countries citing papers authored by Emilio Mateev
This map shows the geographic impact of Emilio Mateev'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 Emilio Mateev with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Emilio Mateev more than expected).
Fields of papers citing papers by Emilio Mateev
This network shows the impact of papers produced by Emilio Mateev. 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 Emilio Mateev. The network helps show where Emilio Mateev may publish in the future.
Co-authors
The 25 scholars most cited alongside Emilio Mateev, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 68 | |
| 2 | 2023 | 26 | |
| 3 | 2023 | 23 | |
| 4 | 2024 | 20 | |
| 5 | 2022 | 19 | |
| 6 | 2022 | 14 | |
| 7 | 2024 | 13 | |
| 8 | 2022 | 11 | |
| 9 | 2023 | 11 | |
| 10 | 2024 | 10 | |
| 11 | 2024 | 10 | |
| 12 | 2022 | 6 | |
| 13 | 2021 | 6 | |
| 14 | 2025 | 4 | |
| 15 | 2022 | 4 | |
| 16 | 2024 | 3 | |
| 17 | 2022 | 3 | |
| 18 | 2021 | 3 | |
| 19 | 2024 | 3 | |
| 20 | 2025 | 2 |
About Emilio Mateev
Emilio Mateev is a scholar working on Organic Chemistry, Computational Theory and Mathematics, Pharmacology, Molecular Biology and Electrical and Electronic Engineering, having authored 46 papers that have together received 279 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (18 papers), Cholinesterase and Neurodegenerative Diseases (12 papers), Synthesis and biological activity (10 papers), Synthesis and Characterization of Pyrroles (7 papers), Electrochemical sensors and biosensors (6 papers), Multicomponent Synthesis of Heterocycles (6 papers), Free Radicals and Antioxidants (5 papers) and Pharmacogenetics and Drug Metabolism (4 papers). The work is most often cited by research in Organic Chemistry (134 citations), Computational Theory and Mathematics (65 citations), Pharmacology (57 citations), Pharmacology (15 citations) and Toxicology (5 citations). Emilio Mateev has collaborated with scholars based in Bulgaria, Pakistan and India. Frequent co-authors include Alexander Zlatkov, Magdalena Kondeva-Burdina, Virginia Tzankova, Maya Georgieva, Iva Valkova, Ali Irfan, Shubham Sharma, Vasco Azevedo, Khalid Raza and Debmalya Barh. Their work appears in journals such as Molecules, ZooKeys, Pharmaceuticals, Scientific Reports and International Journal of Molecular Sciences.
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.