Jane Apperley

1.6k total citations
28 papers, 1.1k citations indexed

About

Jane Apperley is a scholar working on Hematology, Immunology and Genetics. According to data from OpenAlex, Jane Apperley has authored 28 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Hematology, 8 papers in Immunology and 7 papers in Genetics. Recurrent topics in Jane Apperley's work include Chronic Myeloid Leukemia Treatments (11 papers), Hematopoietic Stem Cell Transplantation (10 papers) and Acute Lymphoblastic Leukemia research (7 papers). Jane Apperley is often cited by papers focused on Chronic Myeloid Leukemia Treatments (11 papers), Hematopoietic Stem Cell Transplantation (10 papers) and Acute Lymphoblastic Leukemia research (7 papers). Jane Apperley collaborates with scholars based in United Kingdom, United States and France. Jane Apperley's co-authors include J. Hermans, Aloïs Gratwohl, Jeff Szer, D Niederwieser, Dietger Niederwieser, Arnon Nagler, Andrea Bacigalupo, Yoshihisa Kodera, Ephraim J. Fuchs and Xiao‐Jun Huang and has published in prestigious journals such as Journal of Clinical Oncology, Blood and Annals of the Rheumatic Diseases.

In The Last Decade

Jane Apperley

27 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jane Apperley United Kingdom 14 845 352 256 218 173 28 1.1k
Andrew Dagis United States 20 897 1.1× 363 1.0× 207 0.8× 329 1.5× 267 1.5× 38 1.4k
Jason Butler Australia 12 595 0.7× 330 0.9× 214 0.8× 210 1.0× 104 0.6× 43 900
Kris Doney United States 14 756 0.9× 275 0.8× 202 0.8× 214 1.0× 158 0.9× 18 902
Riccardo Varaldo Italy 22 1.1k 1.3× 357 1.0× 249 1.0× 536 2.5× 298 1.7× 56 1.5k
JF Apperley United Kingdom 16 963 1.1× 317 0.9× 253 1.0× 295 1.4× 361 2.1× 26 1.3k
P. B. Mcglave United States 19 1.3k 1.5× 472 1.3× 357 1.4× 394 1.8× 329 1.9× 24 1.7k
Lydia Jones United Kingdom 11 749 0.9× 268 0.8× 255 1.0× 175 0.8× 92 0.5× 27 922
Sabine Fürst France 16 589 0.7× 177 0.5× 184 0.7× 191 0.9× 141 0.8× 46 727
Giovanni Berisso Italy 16 669 0.8× 173 0.5× 276 1.1× 272 1.2× 170 1.0× 23 1.0k
PB McGlave United States 11 1.0k 1.2× 367 1.0× 319 1.2× 253 1.2× 149 0.9× 13 1.2k

Countries citing papers authored by Jane Apperley

Since Specialization
Citations

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

Fields of papers citing papers by Jane Apperley

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jane Apperley

This figure shows the co-authorship network connecting the top 25 collaborators of Jane Apperley. A scholar is included among the top collaborators of Jane Apperley 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 Jane Apperley. Jane Apperley 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.
Deininger, Michael W., Jane Apperley, Christopher Arthur, et al.. (2024). Ponatinib (PON) in patients (pts) with chronic-phase chronic myeloid leukemia (CP-CML) and the T315I mutation (mut): 4-year results from OPTIC.. Journal of Clinical Oncology. 42(16_suppl). 6501–6501.
2.
Raisi‐Estabragh, Zahra, A. Murphy, Marielle Scherrer‐Crosbie, et al.. (2024). Cardiovascular Considerations Before Cancer Therapy. JACC CardioOncology. 6(5). 631–654. 26 indexed citations
4.
Niederwieser, D, Helen Baldomero, Jeff Szer, et al.. (2016). Hematopoietic stem cell transplantation activity worldwide in 2012 and a SWOT analysis of the Worldwide Network for Blood and Marrow Transplantation Group including the global survey. Bone Marrow Transplantation. 51(6). 778–785. 198 indexed citations
5.
Apperley, Jane, Dietger Niederwieser, Xiao‐Jun Huang, et al.. (2016). Reprint of: Haploidentical Hematopoietic Stem Cell Transplantation: A Global Overview Comparing Asia, the European Union, and the United States. Biology of Blood and Marrow Transplantation. 22(3). S15–S18. 71 indexed citations
6.
Alikian, Mary, Martin Forbes, Gareth Gerrard, et al.. (2016). Next-Generation Sequencing-Assisted DNA-Based Digital PCR for a Personalized Approach to the Detection and Quantification of Residual Disease in Chronic Myeloid Leukemia Patients. Journal of Molecular Diagnostics. 18(2). 176–189. 26 indexed citations
7.
Apperley, Jane, Dietger Niederwieser, Xiao‐Jun Huang, et al.. (2015). Haploidentical Hematopoietic Stem Cell Transplantation: A Global Overview Comparing Asia, the European Union, and the United States. Biology of Blood and Marrow Transplantation. 22(1). 23–26. 67 indexed citations
8.
Haynes, Richard, et al.. (2013). Donor lymphocyte collections using the spectra Optia MNC version 5. Transfusion and Apheresis Science. 48(2). 171–171. 12 indexed citations
9.
Gerrard, Gareth, Pierre Foskett, David Stevens, et al.. (2012). Fast‐mode duplex qPCR for BCR‐ABL1 molecular monitoring: Innovation, automation, and harmonization. American Journal of Hematology. 87(7). 717–720. 11 indexed citations
10.
Walz, Christoph, J Score, Daniela Cilloni, et al.. (2008). The molecular anatomy of the FIP1L1-PDGFRA fusion gene. Leukemia. 23(2). 271–278. 15 indexed citations
11.
Weisdorf, Daniel J., et al.. (2007). Radiation Emergencies: Evaluation, Management, and Transplantation. Biology of Blood and Marrow Transplantation. 13. 103–106. 6 indexed citations
13.
Clark, Richard E., Jo Hermans, J. Alejandro Madrigal, et al.. (2001). HLA‐A3 increases and HLA‐DR1 decreases the risk of acute graft‐versus‐host disease after HLA‐matched sibling bone marrow transplantation for chronic myelogenous leukaemia. British Journal of Haematology. 114(1). 36–41. 19 indexed citations
14.
Mughal, Tariq I., Agnes S. M. Yong, Richard Szydlo, et al.. (2001). Molecular studies in patients with chronic myeloid leukaemia in remission 5 years after allogeneic stem cell transplant define the risk of subsequent relapse. British Journal of Haematology. 115(3). 569–574. 48 indexed citations
15.
Gratwohl, Aloïs, J. Hermans, D Niederwieser, et al.. (2001). Female donors influence transplant-related mortality and relapse incidence in male recipients of sibling blood and marrow transplants. The Hematology Journal. 2(6). 363–370. 96 indexed citations
16.
Pocock, Christopher, Richard Szydlo, John Davis, et al.. (2001). Stem cell transplantation for chronic myeloid leukaemia: the role of infused marrow cell dose. The Hematology Journal. 2(4). 265–272. 8 indexed citations
17.
Ratnavel, R., P Watkins, D Samson, et al.. (1999). Extracorporeal photopheresis (ECP) in the treatment of chronic graft-versus-host disease (GVHD). Bone Marrow Transplantation. 23(9). 881–887. 138 indexed citations
19.
Pfeiffer, Stefan, Diana Samson, Jane Apperley, & Roger Gooding. (1997). Ex vivo generation and function of dendritic cells in multiple myeloma. Biochemical Society Transactions. 25(2). 364S–364S. 1 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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