Ivan Varga

219 papers receiving 3.7k citations

Ivan Varga's Hit Papers

Ki67, PCNA, and MCM proteins: Markers of proliferation in the diagnosis of breast cancer 2016 · 478 citations
4780+3+6Years since publication100200300400

Peers

Ivan Varga
Comparison fields: 5 of 166
  • Parasitology 532
  • Health Informatics 103
  • General Dentistry 88
  • Anatomy 63
  • Infectious Diseases 582
Replace Steven Dow with:
Steven Dow United States
Robert Klopfleisch Germany
Ichiro Takahashi Japan
Andrew S. MacDonald United Kingdom
Luisa Barzon Italy
Mauro Tognon Italy
Reinhard Pabst Germany
Robert N. Moore United States
Yoh‐ichi Tagawa Japan
Tilo Biedermann Germany
Ivan Varga relative to Steven Dow United States Steven Dow's profile →
Citations per field
00.5×10×20×31.5×
Steven Dow · 1×
Citations per year

Countries citing papers authored by Ivan Varga

Since Specialization
Citations

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

Fields of papers citing papers by Ivan Varga

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ivan Varga, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ivan Varga Line = papers co-authored together Ivan Varga links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 244 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Ki67, PCNA, and MCM proteins: Markers of proliferation in the diagnosis of breast cancer
Hit paper breakdown →
2016478
2 2022128
3 2000114
4 2011113
5 200398
6 200585
7 201879
8 202172
9 200565
10
Congenital anomalies of the spleen from an embryological point of view.
200959
11 201953
12 201752
13 201151
14 200750
15 200348
16 200147
17 202144
18 200944
19 201041
20 202038

About Ivan Varga

Ivan Varga is a scholar working on Surgery, Parasitology, Infectious Diseases, Immunology and Molecular Biology, having authored 244 papers that have together received 3.8k indexed citations. Recurring topics across this work include Parasitic Infections and Diagnostics (18 papers), Coccidia and coccidiosis research (17 papers), Tissue Engineering and Regenerative Medicine (16 papers), Mesenchymal stem cell research (15 papers), Reproductive System and Pregnancy (15 papers), Medical and Biological Sciences (12 papers), Reproductive Biology and Fertility (11 papers) and Gynecological conditions and treatments (10 papers). The work is most often cited by research in Parasitology (532 citations), Health Informatics (103 citations), General Dentistry (88 citations), Anatomy (63 citations) and Infectious Diseases (582 citations). Ivan Varga has collaborated with scholars based in Slovakia, Hungary and Czechia. Frequent co-authors include Štefan Polák, T. Sréter, Ľuboš Danišovič, Z. Széll, Ľ Danihel, Andrej Thurzo, Martin Klein, David Kachlík, Paulína Gálfiová and Daniel Böhmer. Their work appears in journals such as Physiological Research, Veterinary Parasitology, Annals of Anatomy - Anatomischer Anzeiger, International Journal of Molecular Sciences and Clinical Anatomy.

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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