Eileen M. Boyle

5.5k total citations
84 papers, 1.5k citations indexed

About

Eileen M. Boyle is a scholar working on Hematology, Molecular Biology and Oncology. According to data from OpenAlex, Eileen M. Boyle has authored 84 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 60 papers in Hematology, 37 papers in Molecular Biology and 21 papers in Oncology. Recurrent topics in Eileen M. Boyle's work include Multiple Myeloma Research and Treatments (55 papers), Protein Degradation and Inhibitors (20 papers) and Chronic Lymphocytic Leukemia Research (17 papers). Eileen M. Boyle is often cited by papers focused on Multiple Myeloma Research and Treatments (55 papers), Protein Degradation and Inhibitors (20 papers) and Chronic Lymphocytic Leukemia Research (17 papers). Eileen M. Boyle collaborates with scholars based in United States, France and United Kingdom. Eileen M. Boyle's co-authors include Gareth J. Morgan, Franck Morschhauser, Brian A. Walker, Faith E. Davies, Christopher P. Wardell, Charles Herbaux, Guillaume Marcotte, Claude Négrier, Etienne Hautin and Jean David and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Blood.

In The Last Decade

Eileen M. Boyle

77 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Eileen M. Boyle United States 20 592 530 444 341 341 84 1.5k
James Essell United States 19 673 1.1× 461 0.9× 502 1.1× 286 0.8× 273 0.8× 63 1.4k
Lionel Karlin France 22 922 1.6× 956 1.8× 746 1.7× 313 0.9× 215 0.6× 101 1.8k
Mathias Hänel Germany 21 734 1.2× 247 0.5× 675 1.5× 484 1.4× 814 2.4× 72 1.8k
Francis S. Morrison United States 20 582 1.0× 225 0.4× 344 0.8× 331 1.0× 271 0.8× 54 1.3k
Pascal Lenain France 14 859 1.5× 683 1.3× 662 1.5× 336 1.0× 338 1.0× 40 1.3k
Rudolf Pihusch Germany 21 685 1.2× 253 0.5× 211 0.5× 141 0.4× 47 0.1× 43 1.2k
J. Rifón Spain 18 515 0.9× 641 1.2× 316 0.7× 361 1.1× 253 0.7× 60 1.5k
Maro Ohanian United States 24 1.2k 2.1× 678 1.3× 306 0.7× 528 1.5× 130 0.4× 120 1.8k
David Westerman Australia 27 732 1.2× 576 1.1× 776 1.7× 1.4k 4.2× 1.4k 4.1× 125 2.8k
Canellos Gp United States 20 516 0.9× 116 0.2× 361 0.8× 412 1.2× 477 1.4× 49 1.3k

Countries citing papers authored by Eileen M. Boyle

Since Specialization
Citations

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

Fields of papers citing papers by Eileen M. Boyle

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Eileen M. Boyle. 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 Eileen M. Boyle. The network helps show where Eileen M. Boyle may publish in the future.

Co-authorship network of co-authors of Eileen M. Boyle

This figure shows the co-authorship network connecting the top 25 collaborators of Eileen M. Boyle. A scholar is included among the top collaborators of Eileen M. Boyle 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 Eileen M. Boyle. Eileen M. Boyle 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.
Andonian, Brian J., Joseph A. Hippensteel, Katrina Abuabara, et al.. (2024). Inflammation and aging-related disease: A transdisciplinary inflammaging framework. GeroScience. 47(1). 515–542. 19 indexed citations
2.
Yong, Kwee, Karthik Ramasamy, Simon Stern, et al.. (2024). Diagnosis and management of smouldering myeloma: A British Society for Haematology Good Practice Paper. British Journal of Haematology. 204(4). 1193–1206. 1 indexed citations
3.
Boyle, Eileen M., Lydia Lee, Dean Smith, et al.. (2024). Challenges in designing and running smouldering myeloma interventional clinical trials. SHILAP Revista de lepidopterología. 5(2). 418–420. 1 indexed citations
4.
Chojnacka, Monika, Benjamin Diamond, Bachisio Ziccheddu, et al.. (2023). Impact of Rare Structural Variant Events in Newly Diagnosed Multiple Myeloma. Clinical Cancer Research. 30(3). 575–585. 1 indexed citations
5.
6.
Agarwal, Gaurav, Lisa Ferguson, Jaimal Kothari, et al.. (2023). Targeted NGS Panel Guides Risk-Adapted Treatment Intention in Newly Diagnosed Myeloma Patients. Blood. 142(Supplement 1). 644–644. 1 indexed citations
7.
Fréalle, Émilie, Hélène Demarquette, Charles Herbaux, et al.. (2021). Case Report: Two Cases of Cryptosporidiosis in Heavily Pretreated Patients With Myeloma. Clinical Lymphoma Myeloma & Leukemia. 21(6). e545–e547. 3 indexed citations
8.
Boyle, Eileen M., Patrick Blaney, Yubao Wang, et al.. (2021). Unifying the Definition of High-Risk in Multiple Myeloma. Blood. 138(Supplement 1). 2714–2714.
9.
Maura, Francesco, Eileen M. Boyle, Even H Rustad, et al.. (2021). Chromothripsis as a pathogenic driver of multiple myeloma. Seminars in Cell and Developmental Biology. 123. 115–123. 25 indexed citations
10.
Maclachlan, Kylee, Even H Rustad, Andriy Derkach, et al.. (2021). Copy number signatures predict chromothripsis and clinical outcomes in newly diagnosed multiple myeloma. Nature Communications. 12(1). 5172–5172. 26 indexed citations
11.
Deshpande, Shayu, Ruslana G. Tytarenko, Yan Wang, et al.. (2020). Monitoring treatment response and disease progression in myeloma with circulating cell‐free DNA. European Journal Of Haematology. 106(2). 230–240. 22 indexed citations
12.
Renaud, Loïc, Louis Terriou, Nathalie Cambier, et al.. (2020). Treatment with Temozolomide and Ibrutinib in Recurrent/Refractory Primary (PCNSL) and Secondary CNS Lymphoma (SCNSL). Blood. 136(Supplement 1). 23–24. 7 indexed citations
13.
Rustad, Even H. & Eileen M. Boyle. (2020). Monitoring minimal residual disease in the bone marrow using next generation sequencing. Best Practice & Research Clinical Haematology. 33(1). 101149–101149. 13 indexed citations
14.
15.
Bauer, Michael, Cody Ashby, Christopher P. Wardell, et al.. (2020). Differential RNA splicing as a potentially important driver mechanism in multiple myeloma. Haematologica. 106(3). 736–745. 22 indexed citations
16.
Poulain, Stéphanie, Christophe Roumier, Martin Figeac, et al.. (2015). Genomic Landscape of CXCR4 Mutations in Waldenström Macroglobulinemia. Clinical Cancer Research. 22(6). 1480–1488. 82 indexed citations
17.
Boyle, Eileen M., Guillemette Fouquet, Salomon Manier, et al.. (2014). Myélome, IMiD et thrombose. 20(1). 15–22. 1 indexed citations
18.
Poulain, Stéphanie, Charles Herbaux, Elisabeth Bertrand, et al.. (2013). Genomic Studies Have Identified Multiple Mechanisms of Genetic Changes in Waldenström Macroglobulinemia. Clinical Lymphoma Myeloma & Leukemia. 13(2). 202–204. 6 indexed citations
19.
Boyle, Eileen M., Guillemette Fouquet, Salomon Manier, et al.. (2012). Immunomodulator drug-based therapy in myeloma and the occurrence of thrombosis. Expert Review of Hematology. 5(6). 619–629. 14 indexed citations
20.
Wémeau, Mathieu, Laurent Pascal, Bénédicte Hivert, et al.. (2011). Prognostic value of PINI index in patients with multiple myeloma. European Journal Of Haematology. 88(4). 306–313. 19 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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