Ivan Matić
- Physiology top 0.5%
- Oncology top 1%
- PARP inhibition in cancer therapy 14
- Molecular Biology top 2%
- Ubiquitin and proteasome pathways 14
- RNA and protein synthesis mechanisms 8
- Glycosylation and Glycoproteins Research 7
- DNA Repair Mechanisms 6
- Immunology top 5%
- Toxin Mechanisms and Immunotoxins 13
- Parasitology top 5%
-
- Advanced Proteomics Techniques and Applications 8
- Mass Spectrometry Techniques and Applications 5
- Co-authors
- Matthias MannRonald T. HayMichael H. TathamThomas ColbyJürgen CoxIvan AhelJuán José BonfiglioMaximiliane Hilger
- Cited by
- PhysiologyOncologyMolecular Biology
- Journals
- Molecular Cell (5 papers)Nature Communications (4 papers)Journal of Biological Chemistry (3 papers)
- Partner nations
- GermanyUnited KingdomNetherlands
In The Last Decade
Ivan Matić
44 papers receiving 4.4k citations
Hit Papers
Peers
Comparison fields: 5 of 110
- Physiology 340
- Oncology 1.8k
- Molecular Biology 3.4k
- Immunology 790
- Parasitology 166
Countries citing papers authored by Ivan Matić
This map shows the geographic impact of Ivan Matić'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 Matić with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ivan Matić more than expected).
Fields of papers citing papers by Ivan Matić
This network shows the impact of papers produced by Ivan Matić. 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 Matić. The network helps show where Ivan Matić may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ivan Matić, 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 | 1 | |
| 2 | 2025 | 4 | |
| 3 | 2025 | 2 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 5 | |
| 6 | 2023 | 44 | |
| 7 | 2023 | 0 | |
| 8 | 2023 | 2 | |
| 9 | 2022 | 24 | |
| 10 | 2020 | 72 | |
| 11 | 2018 | 192 | |
| 12 | 2018 | 85 | |
| 13 | 2017 | 272 | |
| 14 | 2016 | 190 | |
| 15 | 2016 | 222 | |
| 16 | 2015 | 76 | |
| 17 | 2014 | 14 | |
| 18 | 2010 | 260 | |
| 19 | 2010 | 133 | |
| 20 | 2008 | 134 |
About Ivan Matić
Ivan Matić is a scholar working on Physiology, Immunology, Oncology, Endocrinology and Spectroscopy, having authored 45 papers that have together received 4.4k indexed citations. Recurring topics across this work include Ubiquitin and proteasome pathways (14 papers), PARP inhibition in cancer therapy (14 papers), Toxin Mechanisms and Immunotoxins (13 papers), Advanced Proteomics Techniques and Applications (8 papers), RNA and protein synthesis mechanisms (8 papers), Glycosylation and Glycoproteins Research (7 papers), DNA Repair Mechanisms (6 papers) and Mass Spectrometry Techniques and Applications (5 papers). The work is most often cited by research in Physiology (340 citations), Oncology (1.8k citations), Molecular Biology (3.4k citations), Immunology (790 citations) and Parasitology (166 citations). Ivan Matić has collaborated with scholars based in Germany, United Kingdom and Netherlands. Frequent co-authors include Matthias Mann, Ronald T. Hay, Michael H. Tatham, Thomas Colby, Jürgen Cox, Ivan Ahel, Juán José Bonfiglio, Maximiliane Hilger, Orsolya Leidecker and Nagarjuna Nagaraj. Their work appears in journals such as Molecular Cell, Nature Communications, Journal of Biological Chemistry, Science Signaling and Journal of Proteome Research.
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.