Ivan Protsyuk
Impact in
- Health Informatics top 1%
- Artificial Intelligence in Healthcare and Education
- Nephrology top 5%
- Acute Kidney Injury Research
Papers in
-
- Metabolomics and Mass Spectrometry Studies 6
- Gut microbiota and health 4
- Co-authors
- Pieter C. Dorrestein (6 shared papers)Theodore Alexandrov (6 shared papers)Ricardo da Silva (3 shared papers)Louis-Félix Nothias-Scaglia (2 shared papers)Mingxun Wang (2 shared papers)Julien Paolini (1 shared paper)Marc Litaudon (1 shared paper)David Touboul (1 shared paper)
- Journals
- Analytical Chemistry (2 papers)Nature Protocols (2 papers)Cell Host & Microbe (1 paper)Nature Methods (1 paper)Nature (1 paper)
- Partner nations
- United StatesGermanyUnited Kingdom
In The Last Decade
Ivan Protsyuk
12 papers receiving 2.7k citations
Ivan Protsyuk's Hit Papers
Peers
Comparison fields: 5 of 162
- Health Informatics 140
- Nephrology 218
- Health Information Management 107
- Pharmacology 335
- Biotechnology 146
Countries citing papers authored by Ivan Protsyuk
This map shows the geographic impact of Ivan Protsyuk'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 Ivan Protsyuk with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ivan Protsyuk more than expected).
Fields of papers citing papers by Ivan Protsyuk
This network shows the impact of papers produced by Ivan Protsyuk. 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 Ivan Protsyuk. The network helps show where Ivan Protsyuk may publish in the future.
Co-authors
The 25 scholars most cited alongside Ivan Protsyuk, 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 | Feature-based molecular networking in the GNPS analysis environment Hit paper breakdown → | 2020 | 1132 |
| 2 | A clinically applicable approach to continuous prediction of future acute kidney injury Hit paper breakdown → | 2019 | 753 |
| 3 | Bioactivity-Based Molecular Networking for the Discovery of Drug Leads in Natural Product Bioassay-Guided Fractionation Hit paper breakdown → | 2018 | 326 |
| 4 | 2017 | 98 | |
| 5 | 2017 | 79 | |
| 6 | 2017 | 75 | |
| 7 | 2021 | 67 | |
| 8 | 2017 | 60 | |
| 9 | 2016 | 39 | |
| 10 | 2018 | 31 | |
| 11 | 2019 | 24 | |
| 12 | 2021 | 12 |
About Ivan Protsyuk
Ivan Protsyuk is a scholar working on Molecular Biology, Molecular Medicine, Clinical Biochemistry, Nephrology and Ecology, having authored 12 papers that have together received 2.7k indexed citations. Recurring topics across this work include Metabolomics and Mass Spectrometry Studies (6 papers), Gut microbiota and health (4 papers), Microbial Community Ecology and Physiology (2 papers), Advanced Chemical Sensor Technologies (2 papers), Sepsis Diagnosis and Treatment (2 papers), Machine Learning in Healthcare (2 papers), Plant-based Medicinal Research (1 paper) and Chronic Kidney Disease and Diabetes (1 paper). The work is most often cited by research in Health Informatics (140 citations), Nephrology (218 citations), Health Information Management (107 citations), Pharmacology (335 citations) and Biotechnology (146 citations). Ivan Protsyuk has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Pieter C. Dorrestein, Theodore Alexandrov, Ricardo da Silva, Louis-Félix Nothias-Scaglia, Mingxun Wang, Julien Paolini, Marc Litaudon, David Touboul, Mélissa Nothias-Esposito and Pieter Leyssen. Their work appears in journals such as Analytical Chemistry, Nature Protocols, Cell Host & Microbe, Nature Methods and Nature.
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.