Norbert Vey

24.6k total citations · 1 hit paper
402 papers, 10.6k citations indexed

About

Norbert Vey is a scholar working on Hematology, Molecular Biology and Genetics. According to data from OpenAlex, Norbert Vey has authored 402 papers receiving a total of 10.6k indexed citations (citations by other indexed papers that have themselves been cited), including 306 papers in Hematology, 106 papers in Molecular Biology and 100 papers in Genetics. Recurrent topics in Norbert Vey's work include Acute Myeloid Leukemia Research (236 papers), Acute Lymphoblastic Leukemia research (92 papers) and Hematopoietic Stem Cell Transplantation (91 papers). Norbert Vey is often cited by papers focused on Acute Myeloid Leukemia Research (236 papers), Acute Lymphoblastic Leukemia research (92 papers) and Hematopoietic Stem Cell Transplantation (91 papers). Norbert Vey collaborates with scholars based in France, United States and Italy. Norbert Vey's co-authors include Thomas Prébet, Didier Blaise, Pierre Fenaux, Mohamad Mohty, Catherine Faucher, Véronique Gelsi‐Boyer, Christian Récher, Christian Chabannon, Julien Mozziconacci and Daniel Olive and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Blood.

In The Last Decade

Norbert Vey

394 papers receiving 10.5k citations

Hit Papers

Bromodomain inhibitor OTX... 2016 2026 2019 2022 2016 100 200 300

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Norbert Vey 7.1k 3.7k 2.4k 2.3k 2.2k 402 10.6k
Nigel H. Russell 8.9k 1.3× 4.4k 1.2× 3.3k 1.4× 2.5k 1.1× 2.5k 1.1× 355 12.4k
Norbert Ifrah 7.3k 1.0× 3.9k 1.0× 3.5k 1.4× 2.8k 1.2× 1.7k 0.8× 231 11.4k
Peter L. Greenberg 9.1k 1.3× 3.2k 0.9× 1.7k 0.7× 1.4k 0.6× 3.8k 1.7× 203 11.0k
Meir Wetzler 5.0k 0.7× 3.0k 0.8× 2.1k 0.9× 1.9k 0.8× 2.1k 0.9× 245 8.6k
Marcos de Lima 9.2k 1.3× 2.0k 0.5× 3.5k 1.4× 2.8k 1.2× 2.3k 1.0× 421 12.7k
Naval Daver 9.2k 1.3× 5.9k 1.6× 4.5k 1.8× 2.1k 0.9× 3.4k 1.5× 622 14.5k
Selina M. Luger 5.4k 0.8× 2.9k 0.8× 2.9k 1.2× 3.2k 1.4× 1.1k 0.5× 304 9.7k
Tapan M. Kadia 9.8k 1.4× 5.4k 1.5× 2.7k 1.1× 3.0k 1.3× 3.9k 1.8× 778 13.2k
Augustin Ferrant 6.5k 0.9× 2.5k 0.7× 3.1k 1.3× 1.7k 0.7× 2.3k 1.0× 225 10.9k
Börje S. Andersson 9.6k 1.3× 2.1k 0.6× 3.7k 1.5× 2.8k 1.2× 2.3k 1.0× 326 13.4k

Countries citing papers authored by Norbert Vey

Since Specialization
Citations

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

Fields of papers citing papers by Norbert Vey

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Norbert Vey

This figure shows the co-authorship network connecting the top 25 collaborators of Norbert Vey. A scholar is included among the top collaborators of Norbert Vey 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 Norbert Vey. Norbert Vey 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.
Orlanducci, Florence, Amira Ben Amara, Laurent Gorvel, et al.. (2025). CD56neg CD16+ cells represent a distinct mature NK cell subset with altered phenotype and are associated with adverse clinical outcome upon expansion in AML. Frontiers in Immunology. 15. 1487792–1487792. 2 indexed citations
3.
Imbert, Caroline, Nicolas Boucherit, Laurent Gorvel, et al.. (2024). Targeting BTN2A1 Enhances Vγ9Vδ2 T-Cell Effector Functions and Triggers Tumor Cell Pyroptosis. Cancer Immunology Research. 12(12). 1677–1690. 3 indexed citations
4.
Noël, Robin, Christophe Zemmour, Thérèse Aurran‐Schleinitz, et al.. (2023). A phase II study of lenalidomide and rituximab (R2) combination in patients with high-risk refractory/relapsed diffuse large B-cell lymphoma. Hematology. 28(1). 2207948–2207948.
5.
Cervera, Nathalie, Arnaud Guillé, José Adélaı̈de, et al.. (2023). Erythroleukemia: Classification. SHILAP Revista de lepidopterología. 4(2). 450–453. 6 indexed citations
7.
Leblanc, Raphaël, Rania Ghossoub, Armelle Goubard, et al.. (2023). Downregulation of stromal syntenin sustains AML development. EMBO Molecular Medicine. 15(11). e17570–e17570. 6 indexed citations
8.
Amara, Amira Ben, Florence Orlanducci, Norbert Vey, et al.. (2023). Prognostic Immune Effector Signature in Adult Acute Lymphoblastic Leukemia Patients Is Dominated by γδ T Cells. Cells. 12(13). 1693–1693. 3 indexed citations
9.
Garciaz, Sylvain, Colombe Saillard, Yosr Hicheri, et al.. (2022). Azacitidine Plus Venetoclax for the Treatment of Relapsed and Newly Diagnosed Acute Myeloid Leukemia Patients. Cancers. 14(8). 2025–2025. 36 indexed citations
10.
Strickland, Stephen A. & Norbert Vey. (2022). Diagnosis and treatment of therapy-related acute myeloid leukemia. Critical Reviews in Oncology/Hematology. 171. 103607–103607. 46 indexed citations
11.
Devillier, Raynier, Lionel Galicier, Gilles Piana, et al.. (2022). Hepatic haemophagocytosis in haematology patients with hepatic dysfunction: prognostic impact and contribution of liver biopsy combined with the haemophagocytic syndrome diagnostic score (HScore). British Journal of Haematology. 199(1). 106–116. 2 indexed citations
12.
Devillier, Raynier, Édouard Forcade, Alice Garnier, et al.. (2021). In-depth time-dependent analysis of the benefit of allo-HSCT for elderly patients with CR1 AML: a FILO study. Blood Advances. 6(6). 1804–1812. 17 indexed citations
13.
Vey, Norbert. (2020). Low-intensity regimens versus standard-intensity induction strategies in acute myeloid leukemia. Therapeutic Advances in Hematology. 11. 154204786–154204786. 15 indexed citations
14.
Grandis, Maria De, Florence Bardin, Cyril Fauriat, et al.. (2017). JAM-C Identifies Src Family Kinase-Activated Leukemia-Initiating Cells and Predicts Poor Prognosis in Acute Myeloid Leukemia. Cancer Research. 77(23). 6627–6640. 18 indexed citations
15.
Griessinger, Emmanuel, Fernando Anjos‐Afonso, Jacques Vargaftig, et al.. (2016). Frequency and Dynamics of Leukemia-Initiating Cells during Short-term Ex Vivo Culture Informs Outcomes in Acute Myeloid Leukemia Patients. Cancer Research. 76(8). 2082–2086. 19 indexed citations
17.
Bally, Cécile, Jehane Fadlallah, Guy Leverger, et al.. (2012). Outcome of Acute Promyelocytic Leukemia (APL) in Children and Adolescents: An Analysis in Two Consecutive Trials of the European APL Group. Journal of Clinical Oncology. 30(14). 1641–1646. 32 indexed citations
18.
Natarajan‐Amé, Shanti, Sophie Park, Lionel Adès, et al.. (2012). Bortezomib combined with low‐dose cytarabine in Intermediate‐2 and high risk myelodysplastic syndromes. A phase I / II Study by the GFM. British Journal of Haematology. 158(2). 232–237. 12 indexed citations
19.
Adès, Lionel, Simone Boehrer, Thomas Prébet, et al.. (2008). Efficacy and safety of lenalidomide in intermediate-2 or high-risk myelodysplastic syndromes with 5q deletion: results of a phase 2 study. Blood. 113(17). 3947–3952. 107 indexed citations
20.
Faucher, Catherine, Anne‐Gaëlle Le Corroller, Christian Chabannon, et al.. (1996). Autologous Transplantation of Blood Stern Cells Mobilized with Filgrastim Alone in 93 Patients with Malignancies: The Number of CD34+ Cells Reinfused Is the Only Factor Predicting Both Granulocyte and Platelet Recovery. Journal of Hematotherapy. 5(6). 663–670. 43 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026