Ivan Đikić
Impact in
- Cell Biology top 0.02%
- Endoplasmic Reticulum Stress and Disease
- Cellular transport and secretion
- Epidemiology top 0.01%
- Autophagy in Disease and Therapy
Papers in
-
- Ubiquitin and proteasome pathways 110
- Protein Kinase Regulation and GTPase Signaling 26
- Epidemiology 97
- Autophagy in Disease and Therapy 92
- Co-authors
- Zvulun Elazar (1 shared paper)Kaisa Haglund (15 shared papers)Vladimir Kirkin (10 shared papers)David G. McEwan (16 shared papers)Fumiyo Ikeda (11 shared papers)Doris Popovic (8 shared papers)Koraljka Husnjak (9 shared papers)Alexandra Stolz (7 shared papers)
- Journals
- Journal of Biological Chemistry (27 papers)Molecular Cell (14 papers)EMBO Reports (11 papers)Nature (11 papers)Nature Cell Biology (9 papers)
- Partner nations
- GermanyUnited StatesCroatia
In The Last Decade
Ivan Đikić
291 papers receiving 42.0k citations
Ivan Đikić's Hit Papers
Peers
Comparison fields: 5 of 172
- Cell Biology 8.9k
- Epidemiology 14.7k
- Physiology 2.1k
- Molecular Biology 26.9k
- Immunology 5.8k
Countries citing papers authored by Ivan Đikić
This map shows the geographic impact of Ivan Đikić'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 Đikić with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ivan Đikić more than expected).
Fields of papers citing papers by Ivan Đikić
This network shows the impact of papers produced by Ivan Đikić. 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 Đikić. The network helps show where Ivan Đikić may publish in the future.
Co-authors
The 25 scholars most cited alongside Ivan Đikić, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 296 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Mechanism and medical implications of mammalian autophagy Hit paper breakdown → | 2018 | 2206 |
| 2 | Nix is a selective autophagy receptor for mitochondrial clearance Hit paper breakdown → | 2009 | 1092 |
| 3 | Ubiquitination in disease pathogenesis and treatment Hit paper breakdown → | 2014 | 1077 |
| 4 | Phosphorylation of the Autophagy Receptor Optineurin Restricts Salmonella Growth Hit paper breakdown → | 2011 | 1074 |
| 5 | A Role for Ubiquitin in Selective Autophagy Hit paper breakdown → | 2009 | 1025 |
| 6 | Cargo recognition and trafficking in selective autophagy Hit paper breakdown → | 2014 | 986 |
| 7 | A Role for NBR1 in Autophagosomal Degradation of Ubiquitinated Substrates Hit paper breakdown → | 2009 | 945 |
| 8 | A role for Pyk2 and Src in linking G-protein-coupled receptors with MAP kinase activation Hit paper breakdown → | 1996 | 903 |
| 9 | Proteasomal and Autophagic Degradation Systems Hit paper breakdown → | 2017 | 869 |
| 10 | Cellular quality control by the ubiquitin-proteasome system and autophagy Hit paper breakdown → | 2019 | 868 |
| 11 | Regulation of endoplasmic reticulum turnover by selective autophagy Hit paper breakdown → | 2015 | 742 |
| 12 | Atypical ubiquitin chains: new molecular signals Hit paper breakdown → | 2008 | 697 |
| 13 | Ubiquitin-binding domains — from structures to functions Hit paper breakdown → | 2009 | 692 |
| 14 | Post-translational modifications in signal integration Hit paper breakdown → | 2010 | 678 |
| 15 | Multiple monoubiquitination of RTKs is sufficient for their endocytosis and degradation Hit paper breakdown → | 2003 | 673 |
| 16 | Ubiquitin-Binding Proteins: Decoders of Ubiquitin-Mediated Cellular Functions Hit paper breakdown → | 2012 | 623 |
| 17 | Phosphorylation of OPTN by TBK1 enhances its binding to Ub chains and promotes selective autophagy of damaged mitochondria Hit paper breakdown → | 2016 | 613 |
| 18 | Specific Recognition of Linear Ubiquitin Chains by NEMO Is Important for NF-κB Activation Hit paper breakdown → | 2009 | 613 |
| 19 | Ubiquitylation and cell signaling Hit paper breakdown → | 2005 | 605 |
| 20 | Ubiquitin-Binding Domains in Y-Family Polymerases Regulate Translesion Synthesis Hit paper breakdown → | 2005 | 603 |
About Ivan Đikić
Ivan Đikić is a scholar working on Molecular Biology, Epidemiology, Cell Biology, Oncology and Immunology, having authored 296 papers that have together received 42.6k indexed citations. Recurring topics across this work include Ubiquitin and proteasome pathways (110 papers), Autophagy in Disease and Therapy (92 papers), Cellular transport and secretion (45 papers), Endoplasmic Reticulum Stress and Disease (28 papers), interferon and immune responses (26 papers), Protein Kinase Regulation and GTPase Signaling (26 papers), Peptidase Inhibition and Analysis (22 papers) and Cancer-related Molecular Pathways (19 papers). The work is most often cited by research in Cell Biology (8.9k citations), Epidemiology (14.7k citations), Physiology (2.1k citations), Molecular Biology (26.9k citations) and Immunology (5.8k citations). Ivan Đikić has collaborated with scholars based in Germany, United States and Croatia. Frequent co-authors include Zvulun Elazar, Kaisa Haglund, Vladimir Kirkin, David G. McEwan, Fumiyo Ikeda, Doris Popovic, Koraljka Husnjak, Alexandra Stolz, Daniela Hoeller and Christian Pohl. Their work appears in journals such as Journal of Biological Chemistry, Molecular Cell, EMBO Reports, Nature and Nature Cell Biology.
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.