Ewgenij Proschak
Impact in
- Computational Theory and Mathematics top 0.2%
- Computational Drug Discovery Methods
- Biochemistry top 0.5%
- Eicosanoids and Hypertension Pharmacology
Papers in
- Biochemistry 42
- Eicosanoids and Hypertension Pharmacology 40
-
- Antibiotic Resistance in Bacteria 13
- Co-authors
- Gisbert SchneiderDaniel MerkHolger StarkDieter SteinhilberKerstin HiesingerMikhail KrasavinDmitry Dar’inMartin Weisel
- Journals
- Journal of Medicinal Chemistry (27 papers)ChemMedChem (14 papers)ACS Medicinal Chemistry Letters (10 papers)Bioorganic & Medicinal Chemistry Letters (8 papers)Bioorganic & Medicinal Chemistry (7 papers)
- Partner nations
- GermanySwitzerlandUnited States
In The Last Decade
Ewgenij Proschak
165 papers receiving 4.6k citations
Hit Papers
Peers
Comparison fields: 5 of 141
- Computational Theory and Mathematics 1.3k
- Biochemistry 548
- Molecular Medicine 275
- Organic Chemistry 1.4k
- Pharmacology 803
Countries citing papers authored by Ewgenij Proschak
This map shows the geographic impact of Ewgenij Proschak'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 Ewgenij Proschak with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ewgenij Proschak more than expected).
Fields of papers citing papers by Ewgenij Proschak
This network shows the impact of papers produced by Ewgenij Proschak. 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 Ewgenij Proschak. The network helps show where Ewgenij Proschak may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ewgenij Proschak, 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 | 2 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 5 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 14 | |
| 7 | 2024 | 10 | |
| 8 | 2024 | 4 | |
| 9 | 2024 | 31 | |
| 10 | 2023 | 8 | |
| 11 | 2022 | 2 | |
| 12 | 2022 | 4 | |
| 13 | 2021 | 11 | |
| 14 | 2021 | 10 | |
| 15 | 2019 | 3 | |
| 16 | 2014 | 42 | |
| 17 | 2014 | 56 | |
| 18 | 2013 | 23 | |
| 19 | 2010 | 7 | |
| 20 | 2006 | 19 |
About Ewgenij Proschak
Ewgenij Proschak is a scholar working on Biochemistry, Molecular Medicine, Computational Theory and Mathematics, Pharmacology and Pharmacology, having authored 170 papers that have together received 4.7k indexed citations. Recurring topics across this work include Eicosanoids and Hypertension Pharmacology (40 papers), Computational Drug Discovery Methods (35 papers), Peroxisome Proliferator-Activated Receptors (26 papers), Inflammatory mediators and NSAID effects (21 papers), Pharmacogenetics and Drug Metabolism (14 papers), Click Chemistry and Applications (14 papers), Chemical Synthesis and Analysis (14 papers) and Antibiotic Resistance in Bacteria (13 papers). The work is most often cited by research in Computational Theory and Mathematics (1.3k citations), Biochemistry (548 citations), Molecular Medicine (275 citations), Organic Chemistry (1.4k citations) and Pharmacology (803 citations). Ewgenij Proschak has collaborated with scholars based in Germany, Switzerland and United States. Frequent co-authors include Gisbert Schneider, Daniel Merk, Holger Stark, Dieter Steinhilber, Kerstin Hiesinger, Mikhail Krasavin, Dmitry Dar’in, Martin Weisel, Yusuf Tanrıkulu and Manfred Schubert‐Zsilavecz. Their work appears in journals such as Journal of Medicinal Chemistry, ChemMedChem, ACS Medicinal Chemistry Letters, Bioorganic & Medicinal Chemistry Letters and Bioorganic & 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.