Margarete A. Fabre

2.4k total citations · 1 hit paper
18 papers, 422 citations indexed

About

Margarete A. Fabre is a scholar working on Hematology, Cancer Research and Genetics. According to data from OpenAlex, Margarete A. Fabre has authored 18 papers receiving a total of 422 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Hematology, 8 papers in Cancer Research and 6 papers in Genetics. Recurrent topics in Margarete A. Fabre's work include Acute Myeloid Leukemia Research (8 papers), Cancer Genomics and Diagnostics (8 papers) and Myeloproliferative Neoplasms: Diagnosis and Treatment (6 papers). Margarete A. Fabre is often cited by papers focused on Acute Myeloid Leukemia Research (8 papers), Cancer Genomics and Diagnostics (8 papers) and Myeloproliferative Neoplasms: Diagnosis and Treatment (6 papers). Margarete A. Fabre collaborates with scholars based in United Kingdom, France and Australia. Margarete A. Fabre's co-authors include George S. Vassiliou, Muxin Gu, Clea Bárcena, Pedro M. Quirós, Siddhartha Kar, Slavé Petrovski, Jonathan Mitchell, M. S. Vijayabaskar, Ryan Langdon and Stephen Burgess and has published in prestigious journals such as Nature Medicine, Nature Genetics and Blood.

In The Last Decade

Margarete A. Fabre

16 papers receiving 417 citations

Hit Papers

Genome-wide analyses of 200,453 individuals yield new ins... 2022 2026 2023 2024 2022 50 100 150

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Margarete A. Fabre United Kingdom 9 236 171 119 78 53 18 422
Xiaosha Zhang United States 10 359 1.5× 288 1.7× 138 1.2× 33 0.4× 33 0.6× 22 481
Dawn Maze Canada 10 220 0.9× 128 0.7× 99 0.8× 22 0.3× 48 0.9× 62 370
Kazuaki Yokoyama Japan 11 168 0.7× 52 0.3× 140 1.2× 132 1.7× 18 0.3× 54 411
Alexa J. Siddon United States 10 246 1.0× 120 0.7× 86 0.7× 31 0.4× 23 0.4× 60 411
Judith Neukirchen Germany 13 503 2.1× 314 1.8× 190 1.6× 49 0.6× 54 1.0× 26 659
O. Krieger Austria 13 375 1.6× 253 1.5× 123 1.0× 38 0.5× 30 0.6× 41 600
Serguei A. Castañeda United States 10 137 0.6× 157 0.9× 130 1.1× 50 0.6× 16 0.3× 22 400
Salvatore Nicola Bertuccio Italy 10 152 0.6× 49 0.3× 183 1.5× 57 0.7× 18 0.3× 28 365
Ilaria Ambaglio Italy 8 750 3.2× 507 3.0× 164 1.4× 38 0.5× 41 0.8× 15 798
Hege Garelius Sweden 11 494 2.1× 196 1.1× 159 1.3× 42 0.5× 29 0.5× 29 557

Countries citing papers authored by Margarete A. Fabre

Since Specialization
Citations

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

Fields of papers citing papers by Margarete A. Fabre

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Margarete A. Fabre. 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 Margarete A. Fabre. The network helps show where Margarete A. Fabre may publish in the future.

Co-authorship network of co-authors of Margarete A. Fabre

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

All Works

18 of 18 papers shown
1.
Garg, Manik, Dorota Matelska, Oliver S. Burren, et al.. (2024). Disease prediction with multi-omics and biomarkers empowers case–control genetic discoveries in the UK Biobank. Nature Genetics. 56(9). 1821–1831. 33 indexed citations
2.
Vitsios, Dimitrios, Sebastian Wasilewski, Slavé Petrovski, et al.. (2024). Causes and Consequences of Clonal Hematopoiesis with Unknown Drivers in 409,553 Whole-Genome Sequenced UK Biobank Participants. Blood. 144(Supplement 1). 945–945.
3.
Gu, Muxin, William G. Dunn, Ludovica Marando, et al.. (2023). Prevalence and significance of DDX41 gene variants in the general population. Blood. 142(14). 1185–1192. 24 indexed citations
4.
Gu, Muxin, William G. Dunn, Ludovica Marando, et al.. (2023). Multiparameter prediction of myeloid neoplasia risk. Nature Genetics. 55(9). 1523–1530. 46 indexed citations
5.
Chapman, Michael Spencer, Alyssa Cull, Marioara F. Ciuculescu, et al.. (2023). Clonal selection of hematopoietic stem cells after gene therapy for sickle cell disease. Nature Medicine. 29(12). 3175–3183. 27 indexed citations
6.
Stelmach, Patrick, Sarah Richter, Sandra Sauer, et al.. (2023). Clonal hematopoiesis with <i>DNMT3A</i> and <i>PPM1D</i> mutations impairs regeneration in autologous stem cell transplant recipients. Haematologica. 108(12). 3308–3320. 8 indexed citations
7.
Dunn, William G., Muxin Gu, Ludovica Marando, et al.. (2023). Machine Learning for Identification of High-Risk Clonal Haematopoiesis Using Blood Count Data. Blood. 142(Supplement 1). 1318–1318.
8.
Fabre, Margarete A. & George S. Vassiliou. (2023). The lifelong natural history of clonal hematopoiesis and its links to myeloid neoplasia. Blood. 143(7). 573–581. 11 indexed citations
9.
Kar, Siddhartha, Pedro M. Quirós, Muxin Gu, et al.. (2022). Genome-wide analyses of 200,453 individuals yield new insights into the causes and consequences of clonal hematopoiesis. Nature Genetics. 54(8). 1155–1166. 192 indexed citations breakdown →
10.
Fabre, Margarete A., Thomas McKerrell, Maximilian Zwiebel, et al.. (2019). Concordance for clonal hematopoiesis is limited in elderly twins. Blood. 135(4). 269–273. 28 indexed citations
11.
Garbowski, Maciej, Margarete A. Fabre, Patricia Evans, & John B. Porter. (2009). Vitamin C Status in Transfusionally Iron-Overloaded Patients On Long-Term Deferasirox and Its Relationship to Myocardial Iron Removal.. Blood. 114(22). 2005–2005. 2 indexed citations
12.
Fabre, Margarete A., Des C. Jones, Mike Bunce, et al.. (2004). The impact of thiopurine S-methyltransferase polymorphisms on azathioprine dose 1 year after renal transplantation. Transplant International. 17(9). 531–539. 18 indexed citations
13.
Fabre, Margarete A., Des C. Jones, Mike Bunce, et al.. (2004). The impact of thiopurine S-methyltransferase polymorphisms on azathioprine dose 1 year after renal transplantation. Transplant International. 17(9). 531–539. 19 indexed citations
14.
Fabre, Margarete A., et al.. (1994). [Exudative gastropathy associated with cytomegalovirus infection after allogenic bone marrow transplantation].. PubMed. 18(8-9). 775–8. 2 indexed citations
15.
Ekert, Paul G., Jean‐Michel Métreau, Élie Serge Zafrani, et al.. (1991). [Hepatic cholesterol ester storage disease. Two new cases diagnosed in adults].. PubMed. 15(5). 441–4. 1 indexed citations
16.
Messaddeq, Nadia, et al.. (1990). Étude au microscope électronique à balayage des peignes tibiaux chezC. nubeculosus (Diptere, Ceratopogonides). Annales de Parasitologie Humaine et Comparée. 65(2). 94–97. 1 indexed citations
17.
Berson, Alain, Margarete A. Fabre, P Rougier, et al.. (1990). [Unusual cause of ascites: the POEMS syndrome].. PubMed. 14(8-9). 675–9. 6 indexed citations
18.
Pelletier, G., et al.. (1988). [Ileal metastasis of cancer of the amygdaloid body].. PubMed. 12(3). 292–3. 4 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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