Darko Marković

1.6k total citations
18 papers, 1.2k citations indexed

About

Darko Marković is a scholar working on Neurology, Immunology and Molecular Biology. According to data from OpenAlex, Darko Marković has authored 18 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Neurology, 6 papers in Immunology and 5 papers in Molecular Biology. Recurrent topics in Darko Marković's work include Neuroinflammation and Neurodegeneration Mechanisms (7 papers), Immune cells in cancer (5 papers) and Glioma Diagnosis and Treatment (4 papers). Darko Marković is often cited by papers focused on Neuroinflammation and Neurodegeneration Mechanisms (7 papers), Immune cells in cancer (5 papers) and Glioma Diagnosis and Treatment (4 papers). Darko Marković collaborates with scholars based in Germany, United States and Netherlands. Darko Marković's co-authors include Helmut Kettenmann, Michael Synowitz, Rainer Glaß, Nico van Rooijen, Susanne A. Wolf, Frank Szulzewsky, Hendrikus Boddeke, Xi Wang, Bart J. L. Eggen and Thomas Langmann and has published in prestigious journals such as Journal of Neuroscience, PLoS ONE and Cancer Research.

In The Last Decade

Darko Marković

18 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Darko Marković Germany 12 545 471 455 405 205 18 1.2k
Frank Szulzewsky United States 23 851 1.6× 616 1.3× 735 1.6× 664 1.6× 338 1.6× 42 1.9k
Denis Marino Switzerland 8 358 0.7× 406 0.9× 132 0.3× 545 1.3× 221 1.1× 12 1.2k
Wenson D. Rajan Poland 7 372 0.7× 275 0.6× 271 0.6× 244 0.6× 133 0.6× 10 743
Patrick Ventura United States 11 233 0.4× 323 0.7× 104 0.2× 494 1.2× 97 0.5× 11 1.1k
Jack Mottahedeh United States 12 122 0.2× 102 0.2× 180 0.4× 558 1.4× 147 0.7× 14 1.1k
Yajing Mi China 17 213 0.4× 163 0.3× 96 0.2× 495 1.2× 183 0.9× 31 1.1k
Nathalie Chaverot France 14 189 0.3× 340 0.7× 54 0.1× 540 1.3× 262 1.3× 18 1.2k
Hyesook Yoon United States 19 69 0.1× 143 0.3× 351 0.8× 272 0.7× 168 0.8× 30 908
Ryan J. Emnett United States 17 130 0.2× 119 0.3× 403 0.9× 452 1.1× 106 0.5× 19 1.3k
Yifeng Lin China 19 231 0.4× 102 0.2× 68 0.1× 726 1.8× 184 0.9× 42 1.4k

Countries citing papers authored by Darko Marković

Since Specialization
Citations

This map shows the geographic impact of Darko Marković'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 Darko Marković with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Darko Marković more than expected).

Fields of papers citing papers by Darko Marković

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Darko Marković. 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 Darko Marković. The network helps show where Darko Marković may publish in the future.

Co-authorship network of co-authors of Darko Marković

This figure shows the co-authorship network connecting the top 25 collaborators of Darko Marković. A scholar is included among the top collaborators of Darko Marković 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 Darko Marković. Darko Marković is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Synowitz, Michael, et al.. (2020). O-Vanillin Attenuates the TLR2 Mediated Tumor-Promoting Phenotype of Microglia. International Journal of Molecular Sciences. 21(8). 2959–2959. 19 indexed citations
2.
Buonfiglioli, Alice, Ibrahim E. Efe, Dilansu Güneykaya, et al.. (2019). let-7 MicroRNAs Regulate Microglial Function and Suppress Glioma Growth through Toll-Like Receptor 7. Cell Reports. 29(11). 3460–3471.e7. 75 indexed citations
3.
Szulzewsky, Frank, Sonali Arora, Lot D. de Witte, et al.. (2016). Human glioblastoma‐associated microglia/monocytes express a distinct RNA profile compared to human control and murine samples. Glia. 64(8). 1416–1436. 84 indexed citations
4.
Szulzewsky, Frank, Andreas Pelz, Xi Feng, et al.. (2015). Glioma-Associated Microglia/Macrophages Display an Expression Profile Different from M1 and M2 Polarization and Highly Express Gpnmb and Spp1. PLoS ONE. 10(2). e0116644–e0116644. 317 indexed citations
5.
Förstera, Benjamín, Omar Dzaye, Aline Winkelmann, et al.. (2014). Intracellular glycine receptor function facilitates glioma formation in vivo. Journal of Cell Science. 127(Pt 17). 3687–98. 16 indexed citations
6.
Hu, Feng, Min‐Chi Ku, Darko Marković, et al.. (2014). Glioma‐associated microglial MMP9 expression is upregulated by TLR2 signaling and sensitive to minocycline. International Journal of Cancer. 135(11). 2569–2578. 96 indexed citations
7.
Glojnarić, Ines, Snježana Čužić, & Darko Marković. (2013). Evaluation of hydroxypropyl-beta-cyclodextrin (HPβCD) as formulation vehicle for use in general toxicity studies in mice. Toxicology Letters. 221. S93–S93. 1 indexed citations
8.
Čužić, Snježana, Martina Bosnar, Željko Ferenčić, et al.. (2012). Claudin-3 and Clara Cell 10 kDa Protein as Early Signals of Cigarette Smoke–Induced Epithelial Injury along Alveolar Ducts. Toxicologic Pathology. 40(8). 1169–1187. 18 indexed citations
9.
Fučić, Aleksandra, Ranko Stojković, Davor Želježić, et al.. (2010). Transplacental genotoxicity of antiepileptic drugs: Animal model and pilot study on mother/newborn cohort. Reproductive Toxicology. 30(4). 613–618. 11 indexed citations
10.
Synowitz, Michael, Darko Marković, Katyayni Vinnakota, et al.. (2009). Glioma Induce and Exploit Microglial Membrane Type 1 Metalloprotease Expression for Tumor Expansion. Neurosurgery. 65(2). 425–425. 1 indexed citations
11.
Fučić, Aleksandra, Darko Marković, Zdenko Herceg, et al.. (2008). Developmental and transplacental genotoxicology: Fluconazole. Mutation Research/Genetic Toxicology and Environmental Mutagenesis. 657(1). 43–47. 12 indexed citations
12.
Synowitz, Michael, Boris Engels, Darko Marković, et al.. (2008). The Antitumorigenic Response of Neural Precursors Depends on Subventricular Proliferation and Age. Stem Cells. 26(11). 2945–2954. 38 indexed citations
13.
Synowitz, Michael, Rainer Glaß, Katrin Färber, et al.. (2006). A1 Adenosine Receptors in Microglia Control Glioblastoma-Host Interaction. Cancer Research. 66(17). 8550–8557. 70 indexed citations
14.
Marković, Darko, Rainer Glaß, Michael Synowitz, Nico van Rooijen, & Helmut Kettenmann. (2005). Microglia Stimulate the Invasiveness of Glioma Cells by Increasing the Activity of Metalloprotease-2. Journal of Neuropathology & Experimental Neurology. 64(9). 754–762. 246 indexed citations
15.
Glaß, Rainer, Michael Synowitz, Golo Kronenberg, et al.. (2005). Glioblastoma-Induced Attraction of Endogenous Neural Precursor Cells Is Associated with Improved Survival. Journal of Neuroscience. 25(10). 2637–2646. 164 indexed citations
16.
Fučić, Aleksandra, et al.. (2005). Comparison of genomic damage caused by 5-nitrofurantoin in young and adult mice using the in vivo micronucleus assay. Environmental and Molecular Mutagenesis. 46(1). 59–63. 9 indexed citations
17.
Dobranić, Tomislav, et al.. (2002). Wirkung der Cadmiumsalze auf den Hormonplasmaspiegel und auf die pathologischen Veränderungen am Ovarium bei Kaninchenweibchen. Tierärztliche Umschau. 57(10). 539–546. 4 indexed citations
18.
Brajša, Karmen, et al.. (2000). Erythromycin inhibits LPS induced inflammation in rats. 94–94. 1 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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