Ildikó Szalayova

1.3k total citations
18 papers, 962 citations indexed

About

Ildikó Szalayova is a scholar working on Molecular Biology, Genetics and Cellular and Molecular Neuroscience. According to data from OpenAlex, Ildikó Szalayova has authored 18 papers receiving a total of 962 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 6 papers in Genetics and 4 papers in Cellular and Molecular Neuroscience. Recurrent topics in Ildikó Szalayova's work include Mesenchymal stem cell research (5 papers), Angiogenesis and VEGF in Cancer (3 papers) and Erythrocyte Function and Pathophysiology (2 papers). Ildikó Szalayova is often cited by papers focused on Mesenchymal stem cell research (5 papers), Angiogenesis and VEGF in Cancer (3 papers) and Erythrocyte Function and Pathophysiology (2 papers). Ildikó Szalayova collaborates with scholars based in United States, Hungary and Canada. Ildikó Szalayova's co-authors include Éva Mezey, Sharon Key, G. David Lange, Georgia B. Vogelsang, Barbara J. Crain, Zsuzsanna Tóth, András Bratincsák, Krisztián Németh, Riccardo Cassiani‐Ingoni and Sandra Pastorino and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Blood.

In The Last Decade

Ildikó Szalayova

18 papers receiving 940 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ildikó Szalayova United States 13 377 343 202 198 135 18 962
François Renault-Mihara Japan 15 248 0.7× 458 1.3× 189 0.9× 319 1.6× 173 1.3× 20 1.1k
Shinichi Oka Japan 20 368 1.0× 347 1.0× 141 0.7× 188 0.9× 137 1.0× 59 1.0k
Yahaira Naaldijk United States 19 262 0.7× 472 1.4× 102 0.5× 91 0.5× 146 1.1× 40 1.1k
Nicole Kuzmin‐Nichols United States 19 483 1.3× 334 1.0× 222 1.1× 124 0.6× 121 0.9× 24 1.0k
Hyeonseon Park South Korea 15 217 0.6× 195 0.6× 117 0.6× 256 1.3× 133 1.0× 37 826
Hyung Chun Park South Korea 16 365 1.0× 243 0.7× 164 0.8× 359 1.8× 266 2.0× 23 1.0k
Melody P. Lun United States 7 308 0.8× 577 1.7× 339 1.7× 384 1.9× 70 0.5× 8 1.4k
Makoto Ideguchi Japan 16 246 0.7× 575 1.7× 275 1.4× 326 1.6× 137 1.0× 44 1.1k
Anne DeChant United States 8 242 0.6× 292 0.9× 206 1.0× 123 0.6× 92 0.7× 10 779
Sabine Conrad Germany 24 361 1.0× 603 1.8× 316 1.6× 615 3.1× 322 2.4× 37 1.6k

Countries citing papers authored by Ildikó Szalayova

Since Specialization
Citations

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

Fields of papers citing papers by Ildikó Szalayova

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ildikó Szalayova

This figure shows the co-authorship network connecting the top 25 collaborators of Ildikó Szalayova. A scholar is included among the top collaborators of Ildikó Szalayova 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 Ildikó Szalayova. Ildikó Szalayova 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.
Mayer, Balázs, Lynn Vitale‐Cross, Vamsee D. Myneni, et al.. (2024). Bone marrow stromal cell-derived hepcidin has antimicrobial and immunomodulatory activities. Scientific Reports. 14(1). 3986–3986. 4 indexed citations
2.
Ren, Jiaqiang, Lynn Vitale‐Cross, David F. Stroncek, et al.. (2023). The Potential Use of THP-1, a Monocytic Leukemia Cell Line, to Predict Immune-Suppressive Potency of Human Bone-Marrow Stromal Cells (BMSCs) In Vitro: A Pilot Study. International Journal of Molecular Sciences. 24(17). 13258–13258. 4 indexed citations
3.
Vitale‐Cross, Lynn, et al.. (2022). SARS-CoV-2 entry sites are present in all structural elements of the human glossopharyngeal and vagal nerves: Clinical implications. EBioMedicine. 78. 103981–103981. 27 indexed citations
4.
Myneni, Vamsee D., Ildikó Szalayova, & Éva Mezey. (2021). Differences in Steady-State Erythropoiesis in Different Mouse Bones and Postnatal Spleen. Frontiers in Cell and Developmental Biology. 9. 646646–646646. 7 indexed citations
5.
Mezey, Éva, et al.. (2021). An immunohistochemical study of lymphatic elements in the human brain. Proceedings of the National Academy of Sciences. 118(3). 47 indexed citations
6.
Tóth, Zsuzsanna, Ronen R. Leker, Tal Shahar, et al.. (2010). Bone Marrow-Derived Nonreactive Astrocytes in the Mouse Brain After Permanent Middle Cerebral Artery Occlusion. Stem Cells and Development. 20(3). 539–546. 3 indexed citations
7.
Gautam, Dinesh, Jongrye Jeon, Matthew F. Starost, et al.. (2009). Neuronal M3muscarinic acetylcholine receptors are essential for somatotroph proliferation and normal somatic growth. Proceedings of the National Academy of Sciences. 106(15). 6398–6403. 30 indexed citations
8.
Leker, Ronen R., Zsuzsanna Tóth, Tal Shahar, et al.. (2009). Transforming growth factor α induces angiogenesis and neurogenesis following stroke. Neuroscience. 163(1). 233–243. 46 indexed citations
9.
10.
Tóth, Zsuzsanna, Tal Shahar, Ronen R. Leker, et al.. (2007). Sensitive detection of GFP utilizing tyramide signal amplification to overcome gene silencing. Experimental Cell Research. 313(9). 1943–1950. 19 indexed citations
11.
Mitchell, Kendall, Hsiu‐Ying T. Yang, Philippe A. Tessier, et al.. (2007). Localization of S100A8 and S100A9 expressing neutrophils to spinal cord during peripheral tissue inflammation. Pain. 134(1). 216–231. 28 indexed citations
12.
Clark, J A, Rosemarie B. Flick, Ildikó Szalayova, et al.. (2007). Glucocorticoid modulation of tryptophan hydroxylase-2 protein in raphe nuclei and 5-hydroxytryptophan concentrations in frontal cortex of C57/Bl6 mice. Molecular Psychiatry. 13(5). 498–506. 56 indexed citations
13.
Bratincsák, András, Michael Brownstein, Riccardo Cassiani‐Ingoni, et al.. (2007). CD45-Positive Blood Cells Give Rise to Uterine Epithelial Cells in Mice. Stem Cells. 25(11). 2820–2826. 92 indexed citations
14.
Tran, Simon D., Shohta Kodama, Beatrijs M. Lodde, et al.. (2006). Reversal of Sjögren's-like syndrome in non-obese diabetic mice. Annals of the Rheumatic Diseases. 66(6). 812–814. 29 indexed citations
15.
Faustman, Denise L., Simon D. Tran, Shohta Kodama, et al.. (2006). Comment on Papers by Chong et al ., Nishio et al ., and Suri et al . on Diabetes Reversal in NOD Mice. Science. 314(5803). 1243–1243. 15 indexed citations
16.
Mezey, Éva, Sharon Key, Georgia B. Vogelsang, et al.. (2003). Transplanted bone marrow generates new neurons in human brains. Proceedings of the National Academy of Sciences. 100(3). 1364–1369. 454 indexed citations
17.
Mezey, Éva, Ildikó Szalayova, Sandra Gill, et al.. (2003). Of splice and men: what does the distribution of IKAP mRNA in the rat tell us about the pathogenesis of familial dysautonomia?. Brain Research. 983(1-2). 209–214. 24 indexed citations
18.
Hunyady, Béla, Miklós Palkovits, Gyula Mózsik, et al.. (2001). Susceptibility of dopamine D5 receptor targeted mice to cysteamine. Journal of Physiology-Paris. 95(1-6). 147–151. 8 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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