Daniel Vyoral

1.5k total citations
33 papers, 1.2k citations indexed

About

Daniel Vyoral is a scholar working on Hematology, Nutrition and Dietetics and Genetics. According to data from OpenAlex, Daniel Vyoral has authored 33 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Hematology, 18 papers in Nutrition and Dietetics and 16 papers in Genetics. Recurrent topics in Daniel Vyoral's work include Iron Metabolism and Disorders (19 papers), Trace Elements in Health (18 papers) and Hemoglobinopathies and Related Disorders (14 papers). Daniel Vyoral is often cited by papers focused on Iron Metabolism and Disorders (19 papers), Trace Elements in Health (18 papers) and Hemoglobinopathies and Related Disorders (14 papers). Daniel Vyoral collaborates with scholars based in Czechia, United States and Australia. Daniel Vyoral's co-authors include Jir̆ı́ Petrák, Radek Čmejla, Des R. Richardson, Prem Ponka, Jana Čmejlová, Chris D. Vulpe, Ondřej Toman, Robert Ivánek, Róbert Šuťák and Petr Man and has published in prestigious journals such as Journal of Biological Chemistry, Blood and PLoS ONE.

In The Last Decade

Daniel Vyoral

33 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
Daniel Vyoral Czechia 19 510 466 357 279 124 33 1.2k
Jir̆ı́ Petrák Czechia 25 989 1.9× 561 1.2× 292 0.8× 299 1.1× 128 1.0× 61 2.0k
Ermanna Rovida Italy 20 686 1.3× 738 1.6× 485 1.4× 284 1.0× 146 1.2× 47 1.5k
Nathan E. Hellman United States 12 632 1.2× 355 0.8× 621 1.7× 104 0.4× 123 1.0× 13 1.5k
Hans E. Johansson Sweden 31 1.7k 3.4× 229 0.5× 162 0.5× 166 0.6× 109 0.9× 72 2.7k
Paula G. Fraenkel United States 15 424 0.8× 390 0.8× 233 0.7× 239 0.9× 158 1.3× 25 1.1k
Deborah Chiabrando Italy 18 849 1.7× 376 0.8× 181 0.5× 289 1.0× 184 1.5× 28 1.4k
Jukka Hellman Finland 17 943 1.8× 56 0.1× 111 0.3× 148 0.5× 259 2.1× 32 1.8k
J D Gitlin United States 23 809 1.6× 745 1.6× 1.5k 4.3× 204 0.7× 40 0.3× 32 2.5k
Diane M. Durnam United States 19 893 1.8× 766 1.6× 1.3k 3.7× 83 0.3× 64 0.5× 22 2.9k
Heike Lange France 23 1.8k 3.5× 212 0.5× 444 1.2× 67 0.2× 139 1.1× 32 2.5k

Countries citing papers authored by Daniel Vyoral

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Vyoral

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Vyoral

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Vyoral. A scholar is included among the top collaborators of Daniel Vyoral 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 Daniel Vyoral. Daniel Vyoral 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.
Melenovský, Vojtěch, et al.. (2018). Detection and quantitation of iron in ferritin, transferrin and labile iron pool (LIP) in cardiomyocytes using 55Fe and storage phosphorimaging. Biochimica et Biophysica Acta (BBA) - General Subjects. 1862(12). 2895–2901. 17 indexed citations
2.
Toman, Ondřej, Radovan Fišer, Kateřina Machová Poláková, et al.. (2016). Proteomic analysis of imatinib-resistant CML-T1 cells reveals calcium homeostasis as a potential therapeutic target. Oncology Reports. 36(3). 1258–1268. 7 indexed citations
3.
Huang, Michael, Christopher Austin, Mehmet Akif Sari, et al.. (2013). Hepcidin Bound to α2-Macroglobulin Reduces Ferroportin-1 Expression and Enhances Its Activity at Reducing Serum Iron Levels. Journal of Biological Chemistry. 288(35). 25450–25465. 19 indexed citations
4.
Vyoral, Daniel, et al.. (2012). Nutritional hepatic iron overload is not prevented by parenteral hepcidin substitution therapy in mice. British Journal Of Nutrition. 108(10). 1723–1725. 3 indexed citations
5.
Čmejla, Radek, Jir̆ı́ Petrák, Filipp Savvulidi, et al.. (2010). Human MRCKα is regulated by cellular iron levels and interferes with transferrin iron uptake. Biochemical and Biophysical Research Communications. 395(2). 163–167. 12 indexed citations
6.
Singh, Ajay, Maradumane L. Mohan, Alfred Orina Isaac, et al.. (2009). Prion Protein Modulates Cellular Iron Uptake: A Novel Function with Implications for Prion Disease Pathogenesis. PLoS ONE. 4(2). e4468–e4468. 56 indexed citations
7.
Petrák, Jir̆ı́, Robert Ivánek, Ondřej Toman, et al.. (2008). Déjà vu in proteomics. A hit parade of repeatedly identified differentially expressed proteins. PROTEOMICS. 8(9). 1744–1749. 289 indexed citations
8.
Man, Petr, et al.. (2007). Native proteomic analysis of protein complexes in murine intestinal brush border membranes. PROTEOMICS. 7(1). 121–129. 24 indexed citations
9.
Petrák, Jir̆ı́, et al.. (2007). Proteomic analysis of erythroid differentiation induced by hexamethylene bisacetamide in murine erythroleukemia cells. Experimental Hematology. 35(2). 193–202. 7 indexed citations
10.
Petrák, Jir̆ı́, Petr Man, Radek Čmejla, et al.. (2007). Proteomic analysis of hepatic iron overload in mice suggests dysregulation of urea cycle, impairment of fatty acid oxidation, and changes in the methylation cycle. American Journal of Physiology-Gastrointestinal and Liver Physiology. 292(6). G1490–G1498. 34 indexed citations
11.
Petrák, Jir̆ı́, Petr Halada, Radek Čmejla, et al.. (2007). Iron-independent specific protein expression pattern in the liver of HFE-deficient mice. The International Journal of Biochemistry & Cell Biology. 39(5). 1006–1015. 9 indexed citations
12.
Petrák, Jir̆ı́, et al.. (2006). Proteomic analysis of iron overload in human hepatoma cells. American Journal of Physiology-Gastrointestinal and Liver Physiology. 290(5). G1059–G1066. 26 indexed citations
13.
Petrák, Jir̆ı́ & Daniel Vyoral. (2005). Hephaestin—a ferroxidase of cellular iron export. The International Journal of Biochemistry & Cell Biology. 37(6). 1173–1178. 68 indexed citations
14.
Vyoral, Daniel & Jir̆ı́ Petrák. (2005). Hepcidin: A direct link between iron metabolism and immunity. The International Journal of Biochemistry & Cell Biology. 37(9). 1768–1773. 75 indexed citations
15.
16.
Krijt, Jan, et al.. (2004). Different expression pattern of hepcidin genes in the liver and pancreas of C57BL/6N and DBA/2N mice. Journal of Hepatology. 40(6). 891–896. 40 indexed citations
17.
18.
Vyoral, Daniel, Jir̆ı́ Petrák, Róbert Šuťák, et al.. (2003). Incorporation of iron into Tritrichomonas foetus cell compartments reveals ferredoxin as a major iron-binding protein in hydrogenosomes. Microbiology. 149(7). 1911–1921. 16 indexed citations
19.
Vyoral, Daniel. (2003). Native electrophoretic separation and femtomolar detection of 65Zn-containing proteins by storage phosphorimaging. Journal of Biochemical and Biophysical Methods. 57(2). 177–182. 2 indexed citations
20.
Vyoral, Daniel, et al.. (1998). Separation of cellular iron containing compounds by electrophoresis. Biological Trace Element Research. 61(3). 263–275. 15 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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