Nenad Manevski
- Pharmacology top 2%
- Pharmacogenetics and Drug Metabolism 17
- Oncology top 10%
- Drug Transport and Resistance Mechanisms 7
- Pharmaceutical Science top 10%
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- Computational Drug Discovery Methods 6
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- Analytical Chemistry and Chromatography 5
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- Metabolomics and Mass Spectrometry Studies 3
- Receptor Mechanisms and Signaling 3
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- Machine Learning in Materials Science 3
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- Neonatal Health and Biochemistry 2
- Co-authors
- Moshe FinelJari Yli‐KauhaluomaMarie‐May CoissieuxMohamed Bentires‐AljMilan ObradovićAlexander SchmidtAtul SethiBaptiste Hamelin
- Partner nations
- SwitzerlandFinlandUnited Kingdom
In The Last Decade
Nenad Manevski
23 papers receiving 763 citations
Hit Papers
Peers
Comparison fields: 5 of 94
- Pharmacology 189
- Behavioral Neuroscience 31
- Oncology 236
- Biological Psychiatry 18
- Pharmaceutical Science 36
Countries citing papers authored by Nenad Manevski
This map shows the geographic impact of Nenad Manevski'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 Nenad Manevski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nenad Manevski more than expected).
Fields of papers citing papers by Nenad Manevski
This network shows the impact of papers produced by Nenad Manevski. 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 Nenad Manevski. The network helps show where Nenad Manevski may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Nenad Manevski, 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 | 0 | |
| 2 | 2025 | 1 | |
| 3 | 2024 | 11 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 5 | |
| 6 | 2023 | 3 | |
| 7 | 2022 | 17 | |
| 8 | 2020 | 22 | |
| 9 | 2019 | 12 | |
| 10 | Glucocorticoids promote breast cancer metastasisbreakdown → | 2019 | 296 |
| 11 | 2017 | 4 | |
| 12 | 2014 | 47 | |
| 13 | 2014 | 37 | |
| 14 | 2014 | 26 | |
| 15 | 2013 | 24 | |
| 16 | Activity and Enzyme Kinetics of Human UDP-Glucuronosyltransferases : Studies of Psilocin Glucuronidation and the Effects of Albumin on the Enzyme Kinetic Mechanism | 2013 | 0 |
| 17 | 2012 | 29 | |
| 18 | 2012 | 10 | |
| 19 | 2011 | 47 | |
| 20 | 2009 | 53 |
About Nenad Manevski
Nenad Manevski is a scholar working on Pharmacology, Computational Theory and Mathematics and Spectroscopy, having authored 25 papers that have together received 779 indexed citations. Recurring topics across this work include Pharmacogenetics and Drug Metabolism (17 papers), Drug Transport and Resistance Mechanisms (7 papers), Computational Drug Discovery Methods (6 papers), Analytical Chemistry and Chromatography (5 papers), Metabolomics and Mass Spectrometry Studies (3 papers), Machine Learning in Materials Science (3 papers), Receptor Mechanisms and Signaling (3 papers) and Neonatal Health and Biochemistry (2 papers). The work is most often cited by research in Pharmacology (189 citations), Behavioral Neuroscience (31 citations) and Oncology (236 citations). Nenad Manevski has collaborated with scholars based in Switzerland, Finland and United Kingdom. Frequent co-authors include Moshe Finel, Jari Yli‐Kauhaluoma, Marie‐May Coissieux, Mohamed Bentires‐Alj, Milan Obradović, Alexander Schmidt, Atul Sethi, Baptiste Hamelin, Ryoko Okamoto and Hubertus Kohler. Their work appears in journals such as Nature, PLoS ONE and Journal of 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.