Ivan Matić

6.3k total citations · 1 hit paper
45 papers, 4.4k citations indexed

About

Ivan Matić is a scholar working on Molecular Biology, Oncology and Immunology. According to data from OpenAlex, Ivan Matić has authored 45 papers receiving a total of 4.4k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Molecular Biology, 18 papers in Oncology and 14 papers in Immunology. Recurrent topics in Ivan Matić's work include Ubiquitin and proteasome pathways (14 papers), PARP inhibition in cancer therapy (14 papers) and Toxin Mechanisms and Immunotoxins (13 papers). Ivan Matić is often cited by papers focused on Ubiquitin and proteasome pathways (14 papers), PARP inhibition in cancer therapy (14 papers) and Toxin Mechanisms and Immunotoxins (13 papers). Ivan Matić collaborates with scholars based in Germany, United Kingdom and Netherlands. Ivan Matić's 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 and has published in prestigious journals such as Cell, Nucleic Acids Research and Journal of Biological Chemistry.

In The Last Decade

Ivan Matić

44 papers receiving 4.4k citations

Hit Papers

A practical guide to the MaxQuant computational platform ... 2009 2026 2014 2020 2009 200 400 600

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ivan Matić Germany 28 3.4k 1.8k 790 421 415 45 4.4k
Petra Beli Germany 32 3.8k 1.1× 907 0.5× 419 0.5× 804 1.9× 252 0.6× 71 4.7k
Rachel Toth United Kingdom 43 4.0k 1.2× 776 0.4× 581 0.7× 786 1.9× 76 0.2× 84 5.6k
Éric Bonneil Canada 40 3.4k 1.0× 798 0.4× 1.0k 1.3× 265 0.6× 782 1.9× 104 4.8k
Andrzej Gałat France 25 3.3k 1.0× 950 0.5× 1.1k 1.4× 172 0.4× 70 0.2× 70 3.9k
Sarah Maslen United Kingdom 38 3.7k 1.1× 655 0.4× 304 0.4× 657 1.6× 193 0.5× 78 4.8k
Alain Verreault Canada 36 5.3k 1.5× 573 0.3× 170 0.2× 238 0.6× 82 0.2× 64 5.8k
Helen R. Flynn United Kingdom 27 2.4k 0.7× 602 0.3× 267 0.3× 184 0.4× 46 0.1× 49 3.1k
Konrad Büssow Germany 28 2.5k 0.7× 299 0.2× 392 0.5× 197 0.5× 354 0.9× 62 3.5k
Thomas Arnesen Norway 40 4.8k 1.4× 3.8k 2.1× 153 0.2× 270 0.6× 261 0.6× 107 5.8k
Þorkell Andrésson United States 31 2.3k 0.7× 490 0.3× 417 0.5× 304 0.7× 98 0.2× 75 3.5k

Countries citing papers authored by Ivan Matić

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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 of co-authors of Ivan Matić

This figure shows the co-authorship network connecting the top 25 collaborators of Ivan Matić. A scholar is included among the top collaborators of Ivan Matić based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ivan Matić. Ivan Matić is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Mukherjee, Rukmini, Anshu Bhattacharya, Tineke Veenendaal, et al.. (2025). Phosphoribosyl ubiquitination of SNARE proteins regulates autophagy during Legionella infection. The EMBO Journal. 44(15). 4252–4279. 1 indexed citations
2.
Palumbieri, Maria Dilia, et al.. (2025). Serine ADPr on histones and PARP1 is a cellular target of ester-linked ubiquitylation. Nature Chemical Biology. 21(11). 1762–1772. 4 indexed citations
3.
Chapuis, Catherine, Rebecca Smith, Angela Taddei, et al.. (2025). Single nucleosome imaging reveals principles of transient multiscale chromatin reorganization triggered by histone ADP-ribosylation at DNA lesions. Nature Communications. 16(1). 6652–6652. 2 indexed citations
4.
Mukherjee, Rukmini, Anshu Bhattacharya, Santosh Kumar Kuncha, et al.. (2024). Serine ubiquitination of SQSTM1 regulates NFE2L2-dependent redox homeostasis. Autophagy. 21(2). 407–423. 1 indexed citations
5.
Rack, J.G.M., Kang Zhu, Evgeniia Prokhorova, et al.. (2024). Reversal of tyrosine-linked ADP-ribosylation by ARH3 and PARG. Journal of Biological Chemistry. 300(11). 107838–107838. 5 indexed citations
6.
Dauben, Helen, Anne R. Wondisford, Rebecca Smith, et al.. (2023). Modular antibodies reveal DNA damage-induced mono-ADP-ribosylation as a second wave of PARP1 signaling. Molecular Cell. 83(10). 1743–1760.e11. 44 indexed citations
7.
Dauben, Helen, et al.. (2023). Turning science into cover art. Trends in Biochemical Sciences. 48(12). 1009–1011.
8.
Dauben, Helen, et al.. (2023). A chemical biology/modular antibody platform for ADP-ribosylation signaling. Trends in Biochemical Sciences. 48(10). 910–911. 2 indexed citations
9.
Maleszewska, Monika, Swati Parekh, Ming Yang, et al.. (2022). Hypoxia promotes osteogenesis by facilitating acetyl‐CoA ‐mediated mitochondrial–nuclear communication. The EMBO Journal. 41(23). e111239–e111239. 24 indexed citations
10.
Bonfiglio, Juán José, Orsolya Leidecker, Helen Dauben, et al.. (2020). An HPF1/PARP1-Based Chemical Biology Strategy for Exploring ADP-Ribosylation. Cell. 183(4). 1086–1102.e23. 72 indexed citations
11.
Palazzo, Luca, Orsolya Leidecker, Evgeniia Prokhorova, et al.. (2018). Serine is the major residue for ADP-ribosylation upon DNA damage. eLife. 7. 192 indexed citations
12.
Bartlett, Edward, Juán José Bonfiglio, Evgeniia Prokhorova, et al.. (2018). Interplay of Histone Marks with Serine ADP-Ribosylation. Cell Reports. 24(13). 3488–3502.e5. 85 indexed citations
13.
Bonfiglio, Juán José, Pietro Fontana, Qi Zhang, et al.. (2017). Serine ADP-Ribosylation Depends on HPF1. Molecular Cell. 65(5). 932–940.e6. 272 indexed citations
14.
Leidecker, Orsolya, Juán José Bonfiglio, Thomas Colby, et al.. (2016). Serine is a new target residue for endogenous ADP-ribosylation on histones. Nature Chemical Biology. 12(12). 998–1000. 190 indexed citations
15.
Bhogaraju, Sagar, Sissy Kalayil, Yaobin Liu, et al.. (2016). Phosphoribosylation of Ubiquitin Promotes Serine Ubiquitination and Impairs Conventional Ubiquitination. Cell. 167(6). 1636–1649.e13. 222 indexed citations
16.
Rack, J.G.M., Rosa Morra, Eva Barkauskaite, et al.. (2015). Identification of a Class of Protein ADP-Ribosylating Sirtuins in Microbial Pathogens. Molecular Cell. 59(2). 309–320. 76 indexed citations
17.
Vyas, Sejal, Ivan Matić, Jennifer Rood, et al.. (2014). Family-wide analysis of poly(ADP-ribose) polymerase activity. Nature Communications. 5(1). 4426–4426. 14 indexed citations
18.
Matić, Ivan, Joost Schimmel, Ivo A. Hendriks, et al.. (2010). Site-Specific Identification of SUMO-2 Targets in Cells Reveals an Inverted SUMOylation Motif and a Hydrophobic Cluster SUMOylation Motif. Molecular Cell. 39(4). 641–652. 260 indexed citations
19.
Bienko, Magda, Catherine Green, Simone Sabbioneda, et al.. (2010). Regulation of Translesion Synthesis DNA Polymerase η by Monoubiquitination. Molecular Cell. 37(3). 396–407. 133 indexed citations
20.
Schimmel, Joost, Ivan Matić, Martijn van Hagen, et al.. (2008). The Ubiquitin-Proteasome System Is a Key Component of the SUMO-2/3 Cycle. Molecular & Cellular Proteomics. 7(11). 2107–2122. 134 indexed citations

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.

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