Judit Pápay

443 total citations
31 papers, 338 citations indexed

About

Judit Pápay is a scholar working on Pulmonary and Respiratory Medicine, Oncology and Molecular Biology. According to data from OpenAlex, Judit Pápay has authored 31 papers receiving a total of 338 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Pulmonary and Respiratory Medicine, 15 papers in Oncology and 10 papers in Molecular Biology. Recurrent topics in Judit Pápay's work include Lung Cancer Treatments and Mutations (9 papers), PI3K/AKT/mTOR signaling in cancer (5 papers) and Cancer, Hypoxia, and Metabolism (4 papers). Judit Pápay is often cited by papers focused on Lung Cancer Treatments and Mutations (9 papers), PI3K/AKT/mTOR signaling in cancer (5 papers) and Cancer, Hypoxia, and Metabolism (4 papers). Judit Pápay collaborates with scholars based in Hungary, United States and United Kingdom. Judit Pápay's co-authors include Judit Moldvay, Ildikó Krencz, Anna Sebestyén, Tibor Krenács, László Kopper, Zoltàn Sápi, Béla Molnár, András Khoór, József Furák and Katalin Fábián and has published in prestigious journals such as Scientific Reports, International Journal of Molecular Sciences and British Journal of Cancer.

In The Last Decade

Judit Pápay

30 papers receiving 329 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Judit Pápay Hungary 12 139 135 129 90 29 31 338
Thomas Denize United States 12 129 0.9× 121 0.9× 133 1.0× 98 1.1× 47 1.6× 27 322
Alexander Damanakis Germany 12 96 0.7× 150 1.1× 104 0.8× 104 1.2× 33 1.1× 38 351
Eliseo Mattioli Italy 14 233 1.7× 129 1.0× 102 0.8× 83 0.9× 20 0.7× 19 465
Daniel Lindsay United Kingdom 13 95 0.7× 114 0.8× 190 1.5× 110 1.2× 30 1.0× 42 473
Natalie D. ter Hoeve Netherlands 13 205 1.5× 169 1.3× 90 0.7× 118 1.3× 28 1.0× 31 533
Hyun Min Koh South Korea 12 200 1.4× 97 0.7× 125 1.0× 89 1.0× 27 0.9× 41 427
Quanzhou Peng China 11 232 1.7× 69 0.5× 72 0.6× 121 1.3× 22 0.8× 24 377
Xavier Farré Spain 10 109 0.8× 78 0.6× 78 0.6× 57 0.6× 19 0.7× 28 334
Doris Höflmayer Germany 13 171 1.2× 84 0.6× 98 0.8× 70 0.8× 33 1.1× 22 360
Ka‐Won Noh Germany 13 97 0.7× 204 1.5× 172 1.3× 92 1.0× 31 1.1× 22 402

Countries citing papers authored by Judit Pápay

Since Specialization
Citations

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

Fields of papers citing papers by Judit Pápay

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Judit Pápay

This figure shows the co-authorship network connecting the top 25 collaborators of Judit Pápay. A scholar is included among the top collaborators of Judit Pápay 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 Judit Pápay. Judit Pápay 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.
Dankó, Titanilla, Gábor Petővári, Gyula Végső, et al.. (2024). Tumorigenic role of tacrolimus through mTORC1/C2 activation in post-transplant renal cell carcinomas. British Journal of Cancer. 130(7). 1119–1130. 1 indexed citations
2.
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Petővári, Gábor, Titanilla Dankó, Noémi Nagy, et al.. (2024). mTOR hyperactivity and RICTOR amplification as targets for personalized treatments in malignancies. Pathology & Oncology Research. 30. 1611643–1611643. 1 indexed citations
4.
Dankó, Titanilla, Noémi Nagy, Judit Pápay, et al.. (2024). Increased mTOR activity and RICTOR copy number in small cell lung carcinoma progression. European Journal of Cell Biology. 103(4). 151468–151468. 1 indexed citations
5.
6.
Krencz, Ildikó, et al.. (2024). Rictor—A Mediator of Progression and Metastasis in Lung Cancer. Cancers. 16(3). 543–543. 3 indexed citations
7.
Sápi, Zoltàn, Judit Pápay, Katalin Dezső, et al.. (2023). Case report: Complete and durable response to larotrectinib (TRK inhibitor) in an infant diagnosed with angiosarcoma harbouring a KHDRBS1-NTRK3 fusion gene. Frontiers in Oncology. 13. 999810–999810. 2 indexed citations
8.
Krencz, Ildikó, Titanilla Dankó, Ákos Nagy, et al.. (2023). Novel RICTOR amplification harbouring entities: FISH validation of RICTOR amplification in tumour tissue after next-generation sequencing. Scientific Reports. 13(1). 19610–19610. 7 indexed citations
9.
Tóth, Gábor, Judit Pápay, Ilona Kovalszky, et al.. (2022). Proteomic Analysis of Lung Cancer Types—A Pilot Study. Cancers. 14(11). 2629–2629. 9 indexed citations
10.
Krencz, Ildikó, Titanilla Dankó, Gábor Petővári, et al.. (2022). Metabolic Adaptation as Potential Target in Papillary Renal Cell Carcinomas Based on Their In Situ Metabolic Characteristics. International Journal of Molecular Sciences. 23(18). 10587–10587. 5 indexed citations
11.
Megyesfalvi, Zsolt, Judit Pápay, Ilona Kovalszky, et al.. (2021). EGFR variant allele frequency predicts EGFR-TKI efficacy in lung adenocarcinoma: a multicenter study. Translational Lung Cancer Research. 10(2). 662–674. 15 indexed citations
12.
Sarkadi, Balázs, Katalin Mészáros, Ildikó Krencz, et al.. (2020). Glutaminases as a Novel Target for SDHB-Associated Pheochromocytomas/Paragangliomas. Cancers. 12(3). 599–599. 20 indexed citations
13.
Petővári, Gábor, Titanilla Dankó, Ildikó Krencz, et al.. (2019). Inhibition of Metabolic Shift can Decrease Therapy Resistance in Human High-Grade Glioma Cells. Pathology & Oncology Research. 26(1). 23–33. 16 indexed citations
14.
Fábián, Katalin, József Furák, Péter Várallyay, et al.. (2016). Significance of Primary Tumor Location and Histology for Brain Metastasis Development and Peritumoral Brain Edema in Lung Cancer. Oncology. 91(5). 237–242. 11 indexed citations
15.
Fábián, Katalin, Judit Pápay, József Furák, et al.. (2014). Decreased ERCC1 Expression After Platinum-Based Neoadjuvant Chemotherapy in non-Small Cell Lung Cancer. Pathology & Oncology Research. 21(2). 423–431. 2 indexed citations
16.
Fábián, Katalin, Zsuzsanna Németh, József Furák, et al.. (2014). Protein expression differences between lung adenocarcinoma and squamous cell carcinoma with brain metastasis.. PubMed. 34(10). 5593–7. 9 indexed citations
17.
Baka, Zsuzsanna, Péter Barta, György Losonczy, et al.. (2011). Specific expression of PAD4 and citrullinated proteins in lung cancer is not associated with anti-CCP antibody production. International Immunology. 23(6). 405–414. 25 indexed citations
18.
Pápay, Judit, Zoltàn Sápi, Béla Szende, et al.. (2009). Platinum-Based Chemotherapy in Lung Cancer Affects the Expression of Certain Biomarkers Including ERCC1. Pathology & Oncology Research. 15(3). 445–450. 9 indexed citations
19.
Pápay, Judit, Tibor Krenács, Judit Moldvay, et al.. (2007). Immunophenotypic Profiling of Nonsmall Cell Lung Cancer Progression Using the Tissue Microarray Approach. Applied immunohistochemistry & molecular morphology. 15(1). 19–30. 32 indexed citations
20.
Juhász, Márk, Györgyi Műzes, Zsuzsanna Arányi, et al.. (2006). [Association of coeliac disease and myasthenia gravis].. PubMed. 147(18). 841–4. 3 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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