Sergey Popov

3.9k total citations
48 papers, 1.5k citations indexed

About

Sergey Popov is a scholar working on Molecular Biology, Genetics and Cancer Research. According to data from OpenAlex, Sergey Popov has authored 48 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Molecular Biology, 16 papers in Genetics and 11 papers in Cancer Research. Recurrent topics in Sergey Popov's work include Glioma Diagnosis and Treatment (14 papers), Epigenetics and DNA Methylation (8 papers) and Renal and related cancers (8 papers). Sergey Popov is often cited by papers focused on Glioma Diagnosis and Treatment (14 papers), Epigenetics and DNA Methylation (8 papers) and Renal and related cancers (8 papers). Sergey Popov collaborates with scholars based in United Kingdom, Russia and Germany. Sergey Popov's co-authors include Chris Jones, Safa Al‐Sarraj, Alexa Jury, Dorine A. Bax, Ivo J. Huijbers, Clare M. Isacke, David Robertson, Marjan Iravani, Frank Leithäuser and Peter Mӧller and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Journal of Experimental Medicine and SHILAP Revista de lepidopterología.

In The Last Decade

Sergey Popov

41 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sergey Popov United Kingdom 20 825 358 349 316 202 48 1.5k
Monica Hermanson Sweden 12 635 0.8× 447 1.2× 228 0.7× 307 1.0× 135 0.7× 15 1.2k
Lori Frederick United States 15 1.1k 1.3× 646 1.8× 287 0.8× 523 1.7× 201 1.0× 22 1.7k
Guido Reifenberger Germany 21 1.1k 1.3× 546 1.5× 270 0.8× 443 1.4× 173 0.9× 26 2.1k
Andréï Tchirkov France 22 702 0.9× 479 1.3× 412 1.2× 389 1.2× 173 0.9× 88 1.7k
Rossano Cesari United States 20 1.1k 1.4× 438 1.2× 268 0.8× 664 2.1× 190 0.9× 34 2.1k
Aniello Cerrato Italy 24 957 1.2× 249 0.7× 325 0.9× 668 2.1× 240 1.2× 33 1.7k
Sara Akhavanfard United States 8 801 1.0× 340 0.9× 504 1.4× 356 1.1× 248 1.2× 15 1.4k
David Tran United States 20 528 0.6× 568 1.6× 255 0.7× 485 1.5× 253 1.3× 39 1.4k
Elena I. Fomchenko United States 13 773 0.9× 582 1.6× 388 1.1× 605 1.9× 139 0.7× 23 1.5k
Gunnar Wrobel Germany 19 758 0.9× 366 1.0× 287 0.8× 275 0.9× 131 0.6× 21 1.5k

Countries citing papers authored by Sergey Popov

Since Specialization
Citations

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

Fields of papers citing papers by Sergey Popov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sergey Popov

This figure shows the co-authorship network connecting the top 25 collaborators of Sergey Popov. A scholar is included among the top collaborators of Sergey Popov 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 Sergey Popov. Sergey Popov 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
2.
Almeida, Gilberto S., Philippa King, Albert Hallsworth, et al.. (2025). Response of GEM models of neuroblastoma to cabozantinib assessed by multiparametric magnetic resonance imaging. Neoplasia. 65. 101170–101170.
3.
Vasyukova, O. V., et al.. (2024). Identification of novel pathogenic variants in the GNAS gene in children with morbid obesity and pseudohypoparathyroidism. SHILAP Revista de lepidopterología. 21(4). 412–424. 1 indexed citations
4.
Sozaeva, Leila, et al.. (2024). Mild Congenital Hyperinsulinism Caused by Mutation in Human Glucokinase Gene. JCEM Case Reports. 2(12). luae226–luae226.
5.
Belaya, Zhanna, et al.. (2024). Bone Health ECHO Case Report: High Bone Mass in a Patient with Chronic Kidney Disease. Journal of Clinical Densitometry. 28(1). 101554–101554.
6.
Popov, Sergey, et al.. (2024). Factors Affecting Cell Viability during the Enzymatic Dissociation of Human Endocrine Tumor Tissues. Biology. 13(9). 665–665. 1 indexed citations
7.
Eliseeva, Irina A., et al.. (2024). Y-Box-Binding Proteins Have a Dual Impact on Cellular Translation. International Journal of Molecular Sciences. 25(3). 1736–1736. 1 indexed citations
8.
Yukina, M. Yu., et al.. (2023). Clinical Case Report of Non-Diabetic Hypoglycemia Due to a Combination of Germline Mutations in the MEN1 and ABCC8 Genes. Genes. 14(10). 1952–1952. 2 indexed citations
9.
Burford, Anna, Alan Mackay, Sergey Popov, et al.. (2018). The ten-year evolutionary trajectory of a highly recurrent paediatric high grade neuroepithelial tumour with MN1:BEND2 fusion. Scientific Reports. 8(1). 1032–1032. 19 indexed citations
10.
Yogev, Orli, Karen Barker, Gilberto S. Almeida, et al.. (2016). p53 Loss in MYC-Driven Neuroblastoma Leads to Metabolic Adaptations Supporting Radioresistance. Cancer Research. 76(10). 3025–3035. 32 indexed citations
11.
Trabelsi, Saoussen, I. Chabchoub, Anna Burford, et al.. (2016). Molecular Diagnostic and Prognostic Subtyping of Gliomas in Tunisian Population. Molecular Neurobiology. 54(4). 2381–2394. 13 indexed citations
12.
Jamin, Yann, Jessica K.R. Boult, Jin Li, et al.. (2015). Exploring the Biomechanical Properties of Brain Malignancies and Their Pathologic Determinants In Vivo with Magnetic Resonance Elastography. Cancer Research. 75(7). 1216–1224. 89 indexed citations
13.
Trabelsi, Saoussen, Sergey Popov, Anna Burford, et al.. (2015). Meningeal Hemangiopericytomas and Meningomas: a Comparative Immunohistochemical and Genetic Study. Asian Pacific Journal of Cancer Prevention. 16(16). 6871–6876. 16 indexed citations
14.
Bjerke, Lynn, Alan Mackay, Meera Nandhabalan, et al.. (2013). Histone H3.3 Mutations Drive Pediatric Glioblastoma through Upregulation of MYCN. Cancer Discovery. 3(5). 512–519. 226 indexed citations
15.
Little, Suzanne E., Sergey Popov, Alexa Jury, et al.. (2012). Receptor Tyrosine Kinase Genes Amplified in Glioblastoma Exhibit a Mutual Exclusivity in Variable Proportions Reflective of Individual Tumor Heterogeneity. Cancer Research. 72(7). 1614–1620. 93 indexed citations
16.
Moreno, Lucas, et al.. (2012). Role of platelet derived growth factor receptor (PDGFR) over-expression and angiogenesis in ependymoma. Journal of Neuro-Oncology. 111(2). 169–176. 18 indexed citations
17.
Bielen, Aleksandra, Lara Perryman, Gary Box, et al.. (2011). Enhanced Efficacy of IGF1R Inhibition in Pediatric Glioblastoma by Combinatorial Targeting of PDGFRα/β. Molecular Cancer Therapeutics. 10(8). 1407–1418. 41 indexed citations
18.
Williams, Richard D., Reem Al‐Saadi, Tasnim Chagtai, et al.. (2010). Subtype-Specific FBXW7 Mutation and MYCN Copy Number Gain in Wilms' Tumor. Clinical Cancer Research. 16(7). 2036–2045. 55 indexed citations
19.
Gaspar, Nathalie, Swee Y. Sharp, Suzanne A. Eccles, et al.. (2010). Mechanistic Evaluation of the Novel HSP90 Inhibitor NVP-AUY922 in Adult and Pediatric Glioblastoma. Molecular Cancer Therapeutics. 9(5). 1219–1233. 62 indexed citations
20.
Popov, Sergey, Gerhard Moldenhauer, Silke Brüderlein, et al.. (2007). Target Sequence Accessibility Limits Activation-Induced Cytidine Deaminase Activity in Primary Mediastinal B-Cell Lymphoma. Cancer Research. 67(14). 6555–6564. 6 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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