Noémi Nagy

524 total citations
26 papers, 317 citations indexed

About

Noémi Nagy is a scholar working on Molecular Biology, Cancer Research and Genetics. According to data from OpenAlex, Noémi Nagy has authored 26 papers receiving a total of 317 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 11 papers in Cancer Research and 6 papers in Genetics. Recurrent topics in Noémi Nagy's work include PI3K/AKT/mTOR signaling in cancer (11 papers), Lymphoma Diagnosis and Treatment (6 papers) and Chronic Lymphocytic Leukemia Research (5 papers). Noémi Nagy is often cited by papers focused on PI3K/AKT/mTOR signaling in cancer (11 papers), Lymphoma Diagnosis and Treatment (6 papers) and Chronic Lymphocytic Leukemia Research (5 papers). Noémi Nagy collaborates with scholars based in Hungary, United States and Germany. Noémi Nagy's co-authors include Anna Sebestyén, Michel Kahaleh, Michel Cremer, László Kopper, Jacques Devière, Jean‐Luc Van Laethem, Titanilla Dankó, Monika Csóka, Karolina Nemes and Gábor Kovács and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Clinical Oncology and Scientific Reports.

In The Last Decade

Noémi Nagy

24 papers receiving 314 citations

Peers

Noémi Nagy

SURGE

PRM

ONCOL

Ji Shin Lee South Korea

Rumen Kostadinov United States

Magdalena Koczkowska Poland

Enrico Di Oto Italy

Ya-Nong Wang China

Mitsuteru Hiwatari Japan

Sanket Shah India

Xin-Ke Zhang China

Keisuke Nishihara Japan

Ji Shin Lee South Korea

Noémi Nagy

185 ×1.1

93 ×0.9

51 ×0.7

SURGE

114 ×1.7

PRM

81 ×1.4

ONCOL

Citations per year, relative to Noémi Nagy Noémi Nagy (= 1×) peers Ji Shin Lee

Countries citing papers authored by Noémi Nagy

Since Specialization

Citations

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

Fields of papers citing papers by Noémi Nagy

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Noémi Nagy

This figure shows the co-authorship network connecting the top 25 collaborators of Noémi Nagy. A scholar is included among the top collaborators of Noémi Nagy 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 Noémi Nagy. Noémi Nagy is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

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

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

Sayour, Nabil V., Viktória É. Tóth, Zsófia Onódi, et al.. (2023). Droplet Digital PCR Is a Novel Screening Method Identifying Potential Cardiac G-Protein-Coupled Receptors as Candidate Pharmacological Targets in a Rat Model of Pressure-Overload-Induced Cardiac Dysfunction. International Journal of Molecular Sciences. 24(18). 13826–13826. 9 indexed citations

Farkas, Sándor, Daniel Cioca, P. Hornyak, et al.. (2023). Chlorotoxin binds to both matrix metalloproteinase 2 and neuropilin 1. Journal of Biological Chemistry. 299(9). 104998–104998. 9 indexed citations

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

Mikala, Gábor, et al.. (2021). Identification of a novel resistance mechanism in venetoclax treatment and its prediction in chronic lymphocytic leukemia. Acta Oncologica. 60(4). 528–530. 4 indexed citations

Tímár, Botond, et al.. (2021). A hajas sejtes leukémia korszerű diagnosztikája és kezelése. 54(2). 90–102. 1 indexed citations

Krencz, Ildikó, Noémi Nagy, Gábor Petővári, et al.. (2020). Characterization of mTOR Activity and Metabolic Profile in Pediatric Rhabdomyosarcoma. Cancers. 12(7). 1947–1947. 8 indexed citations

Alpár, Donát, Noémi Nagy, Ákos Nagy, et al.. (2019). Dissection of Subclonal Evolution by Temporal Mutation Profiling in Chronic Lymphocytic Leukemia Patients Treated with Ibrutinib. Clinical Lymphoma Myeloma & Leukemia. 19. S279–S279. 3 indexed citations

10.

Nagy, Noémi, et al.. (2018). Release of circulating tumor cells and cell-free nucleic acids is an infrequent event in synovial sarcoma: liquid biopsy analysis of 15 patients diagnosed with synovial sarcoma. Diagnostic Pathology. 13(1). 81–81. 10 indexed citations

11.

Dankó, Titanilla, Gábor Petővári, Noémi Nagy, et al.. (2018). The Effects of Different mTOR Inhibitors in EGFR Inhibitor Resistant Colon Carcinoma Cells. Pathology & Oncology Research. 25(4). 1379–1386. 4 indexed citations

12.

Petővári, Gábor, Ildikó Krencz, Titanilla Dankó, et al.. (2018). Targeting cellular metabolism using rapamycin and/or doxycycline enhances anti-tumour effects in human glioma cells. Cancer Cell International. 18(1). 211–211. 16 indexed citations

13.

Nagy, Noémi, Melinda Hajdu, Csaba Bödör, et al.. (2018). Discrepancy Between Low Levels of mTOR Activity and High Levels of P-S6 in Primary Central Nervous System Lymphoma May Be Explained by PAS Domain-Containing Serine/Threonine-Protein Kinase-Mediated Phosphorylation. Journal of Neuropathology & Experimental Neurology. 77(4). 268–273. 7 indexed citations

14.

Petővári, Gábor, Norbert Szoboszlai, Titanilla Dankó, et al.. (2017). Rapamycin (mTORC1 inhibitor) reduces the production of lactate and 2-hydroxyglutarate oncometabolites in IDH1 mutant fibrosarcoma cells. Journal of Experimental & Clinical Cancer Research. 36(1). 74–74. 18 indexed citations

15.

Nagy, Noémi, et al.. (2016). mTOR activity and its prognostic significance in human colorectal carcinoma depending on C1 and C2 complex-related protein expression. Journal of Clinical Pathology. 70(5). 410–416. 19 indexed citations

16.

Nagy, Noémi, et al.. (2016). Growth inhibitory effect of rapamycin in Hodgkin-lymphoma cell lines characterized by constitutive NOTCH1 activation. Tumor Biology. 37(10). 13695–13704. 3 indexed citations

17.

Sebestyén, Anna, et al.. (2015). Rapamycin can restore the negative regulatory function of transforming growth factor beta 1 in high grade lymphomas. Cytokine. 73(2). 219–224. 8 indexed citations

18.

Nemes, Karolina, Monika Csóka, Noémi Nagy, et al.. (2014). Expression of Certain Leukemia/Lymphoma Related microRNAs and its Correlation with Prognosis in Childhood Acute Lymphoblastic Leukemia. Pathology & Oncology Research. 21(3). 597–604. 49 indexed citations

19.

Nagy, Noémi, Judit Csomor, Lajos Berczi, et al.. (2013). Characteristic mTOR activity in Hodgkin-lymphomas offers a potential therapeutic target in high risk disease – a combined tissue microarray, in vitro and in vivo study. BMC Cancer. 13(1). 250–250. 30 indexed citations

20.

Sebestyén, Anna, Melinda Hajdu, Botond Tímár, et al.. (2012). Activity and complexes of mTOR in diffuse large B-cell lymphomas—a tissue microarray study. Modern Pathology. 25(12). 1623–1628. 24 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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