Ágnes Márk

408 citations
28 papers · 330 · h-index 10

Impact in

    • MicroRNA in disease regulation
    • Cancer, Hypoxia, and Metabolism
    • Chronic Lymphocytic Leukemia Research

Papers in

Ágnes Márk

26 papers receiving 328 citations

Peers

Ágnes Márk
Comparison fields: 5 of 42
  • Cancer Research 51
  • Genetics 31
  • Gastroenterology 16
  • Pathology and Forensic Medicine 34
  • Molecular Biology 121
Replace Valeria Cazzaniga with:
Valeria Cazzaniga Italy
Salih Demir Germany
Felix Seyfried Germany
Ivan Milas Croatia
Stephen K. H. Li Canada
Yongsheng Ruan China
G. Grigoriadis Australia
Jodie Ulaszek United States
Caroline Berglund United States
Hwudaurw Chen United States
Ágnes Márk relative to Valeria Cazzaniga Italy Valeria Cazzaniga's profile →
Citations per field
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Valeria Cazzaniga · 1×
Citations per year

Countries citing papers authored by Ágnes Márk

Since Specialization
Citations

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

Fields of papers citing papers by Ágnes Márk

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ágnes Márk, 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 Ágnes Márk Line = papers co-authored together Ágnes Márk links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201451
2 201332
3 201629
4 201326
5 202125
6 201224
7 201122
8 201221
9 201619
10 201413
11 201810
12 20158
13 20116
14 20226
15 20246
16 20165
17 20165
18 20214
19 20254
20 20163

About Ágnes Márk

Ágnes Márk is a scholar working on Genetics, Pathology and Forensic Medicine, Molecular Biology, Public Health, Environmental and Occupational Health and Hematology, having authored 28 papers that have together received 330 indexed citations. Recurring topics across this work include PI3K/AKT/mTOR signaling in cancer (10 papers), Acute Lymphoblastic Leukemia research (6 papers), Lymphoma Diagnosis and Treatment (4 papers), Chronic Lymphocytic Leukemia Research (3 papers), Multiple Myeloma Research and Treatments (3 papers), Cancer, Hypoxia, and Metabolism (1 paper), TGF-β signaling in diseases (1 paper) and Brain Metastases and Treatment (1 paper). The work is most often cited by research in Cancer Research (51 citations), Genetics (31 citations), Gastroenterology (16 citations), Pathology and Forensic Medicine (34 citations) and Molecular Biology (121 citations). Ágnes Márk has collaborated with scholars based in Hungary, Slovenia and Germany. Frequent co-authors include Anna Réka Sebestyén, László Kopper, Noémi Nagy, Karolina Nemes, Monika Csóka, Gábor Barna, Gábor Kovács, Titanilla Dankó, Ildikó Krencz and István Kenessey. Their work appears in journals such as Pathology & Oncology Research, Hematological Oncology, Modern Pathology, BMC Cancer and American Journal of Clinical Pathology.

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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