Nataliya Gladoun

754 total citations
8 papers, 552 citations indexed

About

Nataliya Gladoun is a scholar working on Molecular Biology, Surgery and Oncology. According to data from OpenAlex, Nataliya Gladoun has authored 8 papers receiving a total of 552 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 2 papers in Surgery and 2 papers in Oncology. Recurrent topics in Nataliya Gladoun's work include Epigenetics and DNA Methylation (4 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and RNA modifications and cancer (1 paper). Nataliya Gladoun is often cited by papers focused on Epigenetics and DNA Methylation (4 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and RNA modifications and cancer (1 paper). Nataliya Gladoun collaborates with scholars based in United States, Spain and Portugal. Nataliya Gladoun's co-authors include Carlos Cordon‐Cardo, Mireia Castillo-Martín, Josep Domingo‐Domenech, Elizabeth Charytonowicz, Dennis M. Bonal, Verónica Rodríguez-Bravo, Samuel J. Vidal, Janis de la Iglesia-Vicente, Daniel P. Petrylak and Mitchell C. Benson and has published in prestigious journals such as PLoS ONE, Cancer Cell and American Journal Of Pathology.

In The Last Decade

Nataliya Gladoun

8 papers receiving 549 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nataliya Gladoun United States 7 334 200 170 125 108 8 552
Marcell A. Szász Hungary 10 210 0.6× 148 0.7× 73 0.4× 128 1.0× 161 1.5× 16 534
Jugang Wu China 16 237 0.7× 197 1.0× 156 0.9× 99 0.8× 97 0.9× 30 518
Zsombor Melegh United Kingdom 11 252 0.8× 90 0.5× 103 0.6× 101 0.8× 50 0.5× 29 433
Jingping Ge China 10 368 1.1× 67 0.3× 102 0.6× 193 1.5× 60 0.6× 38 588
Ye Hu China 11 224 0.7× 80 0.4× 75 0.4× 96 0.8× 48 0.4× 19 374
Nobuyasu Hayashi Japan 11 283 0.8× 188 0.9× 78 0.5× 107 0.9× 144 1.3× 29 565
M.A. Underwood United Kingdom 7 182 0.5× 140 0.7× 149 0.9× 96 0.8× 84 0.8× 10 402
Maria V Yusenko Germany 13 375 1.1× 71 0.4× 268 1.6× 153 1.2× 45 0.4× 22 479
Tisheeka Graham United States 7 429 1.3× 340 1.7× 206 1.2× 173 1.4× 23 0.2× 10 652
C. Magi-Galluzzi United States 7 289 0.9× 98 0.5× 148 0.9× 63 0.5× 31 0.3× 12 455

Countries citing papers authored by Nataliya Gladoun

Since Specialization
Citations

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

Fields of papers citing papers by Nataliya Gladoun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nataliya Gladoun

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

All Works

8 of 8 papers shown
1.
Fernández, Gerardo, Jack Zeineh, Marcel Prastawa, et al.. (2023). Analytical Validation of the PreciseDx Digital Prognostic Breast Cancer Test in Early-Stage Breast Cancer. Clinical Breast Cancer. 24(2). 93–102.e6. 2 indexed citations
2.
Kanagasabai, Thanigaivelan, Guoliang Li, Tian Shen, et al.. (2021). MicroRNA-21 deficiency suppresses prostate cancer progression through downregulation of the IRS1-SREBP-1 signaling pathway. Cancer Letters. 525. 46–54. 34 indexed citations
3.
Donovan, Michael, Gerardo Fernández, Faisal M. Khan, et al.. (2018). Development and validation of a novel automated Gleason grade and molecular profile that define a highly predictive prostate cancer progression algorithm-based test. Prostate Cancer and Prostatic Diseases. 21(4). 594–603. 17 indexed citations
4.
Shukla‐Dave, Amita, Mireia Castillo-Martín, Ming Chen, et al.. (2016). Ornithine Decarboxylase Is Sufficient for Prostate Tumorigenesis via Androgen Receptor Signaling. American Journal Of Pathology. 186(12). 3131–3145. 34 indexed citations
5.
Castillo-Martín, Mireia, et al.. (2015). H-RAS mutation is a key molecular feature of pediatric urothelial bladder cancer. A detailed report of three cases. Journal of Pediatric Urology. 12(2). 91.e1–91.e7. 8 indexed citations
6.
Domingo‐Domenech, Josep, Samuel J. Vidal, Verónica Rodríguez-Bravo, et al.. (2012). Suppression of Acquired Docetaxel Resistance in Prostate Cancer through Depletion of Notch- and Hedgehog-Dependent Tumor-Initiating Cells. Cancer Cell. 22(3). 373–388. 338 indexed citations
7.
Shen, Tian, Nataliya Gladoun, Mireia Castillo-Martín, et al.. (2012). A BAC-Based Transgenic Mouse Specifically Expresses an Inducible Cre in the Urothelium. PLoS ONE. 7(4). e35243–e35243. 14 indexed citations
8.
Karni-Schmidt, Orit, Mireia Castillo-Martín, Tian Shen, et al.. (2011). Distinct Expression Profiles of p63 Variants during Urothelial Development and Bladder Cancer Progression. American Journal Of Pathology. 178(3). 1350–1360. 105 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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Breakdown of academic impact, for papers by Marcell A. Szász Breakdown of academic impact, for papers by Jugang Wu Breakdown of academic impact, for papers by Zsombor Melegh Breakdown of academic impact, for papers by Jingping Ge Breakdown of academic impact, for papers by Ye Hu Breakdown of academic impact, for papers by Nobuyasu Hayashi Breakdown of academic impact, for papers by M.A. Underwood Breakdown of academic impact, for papers by Maria V Yusenko Breakdown of academic impact, for papers by Tisheeka Graham Breakdown of academic impact, for papers by C. Magi-Galluzzi
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2026