Wendy N. Erber

20.3k total citations · 3 hit papers
186 papers, 12.2k citations indexed

About

Wendy N. Erber is a scholar working on Hematology, Genetics and Molecular Biology. According to data from OpenAlex, Wendy N. Erber has authored 186 papers receiving a total of 12.2k indexed citations (citations by other indexed papers that have themselves been cited), including 85 papers in Hematology, 71 papers in Genetics and 57 papers in Molecular Biology. Recurrent topics in Wendy N. Erber's work include Myeloproliferative Neoplasms: Diagnosis and Treatment (37 papers), Acute Myeloid Leukemia Research (35 papers) and Lymphoma Diagnosis and Treatment (22 papers). Wendy N. Erber is often cited by papers focused on Myeloproliferative Neoplasms: Diagnosis and Treatment (37 papers), Acute Myeloid Leukemia Research (35 papers) and Lymphoma Diagnosis and Treatment (22 papers). Wendy N. Erber collaborates with scholars based in Australia, United Kingdom and United States. Wendy N. Erber's co-authors include Anthony R. Green, Karen Pulford, H. Stein, Brunangelo Falini, Linda M. Scott, J L Cordell, D Y Mason, S.M. MacDonald, A K Ghosh and Peter J. Campbell and has published in prestigious journals such as New England Journal of Medicine, The Lancet and Journal of Clinical Oncology.

In The Last Decade

Wendy N. Erber

182 papers receiving 11.9k citations

Hit Papers

Immunoenzymatic labeling of monoclonal antibodies using i... 1984 2026 1998 2012 1984 2005 2007 500 1000 1.5k 2.0k 2.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Wendy N. Erber Australia 40 6.2k 5.0k 4.8k 2.4k 2.0k 186 12.2k
Attilio Orazi United States 49 6.8k 1.1× 8.8k 1.8× 4.5k 0.9× 2.3k 1.0× 2.8k 1.4× 281 16.1k
Alberto Bosi Italy 57 3.6k 0.6× 6.1k 1.2× 2.3k 0.5× 1.0k 0.4× 2.3k 1.2× 321 10.5k
Dieter Hoelzer Germany 62 4.6k 0.7× 7.3k 1.5× 4.6k 1.0× 1.1k 0.5× 4.6k 2.4× 322 16.5k
Robert P. Hasserjian United States 48 6.3k 1.0× 9.3k 1.9× 4.6k 1.0× 1.9k 0.8× 2.9k 1.5× 285 16.2k
Franco Dammacco Italy 72 2.5k 0.4× 5.0k 1.0× 5.9k 1.2× 2.1k 0.9× 4.3k 2.2× 385 17.0k
Daniel A. Arber United States 51 6.3k 1.0× 9.8k 2.0× 4.4k 0.9× 2.5k 1.0× 4.2k 2.1× 266 18.4k
S Tura Italy 65 6.3k 1.0× 10.2k 2.0× 3.7k 0.8× 2.0k 0.8× 4.2k 2.2× 583 17.4k
Marcos González Spain 62 4.1k 0.7× 8.1k 1.6× 5.3k 1.1× 597 0.3× 2.9k 1.5× 376 14.1k
Nicholas C.P. Cross United Kingdom 75 8.5k 1.4× 11.5k 2.3× 7.1k 1.5× 6.4k 2.7× 2.2k 1.1× 395 19.9k
Richard D. Brunning United States 43 3.7k 0.6× 7.4k 1.5× 2.7k 0.6× 1.3k 0.5× 1.5k 0.8× 113 11.4k

Countries citing papers authored by Wendy N. Erber

Since Specialization
Citations

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

Fields of papers citing papers by Wendy N. Erber

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wendy N. Erber. 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 Wendy N. Erber. The network helps show where Wendy N. Erber may publish in the future.

Co-authorship network of co-authors of Wendy N. Erber

This figure shows the co-authorship network connecting the top 25 collaborators of Wendy N. Erber. A scholar is included among the top collaborators of Wendy N. Erber 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 Wendy N. Erber. Wendy N. Erber 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.
Simpson, Alastair G. B., et al.. (2025). Imaging Flow Cytometric Identification of Chromosomal Defects in Paediatric Acute Lymphoblastic Leukaemia. Cells. 14(2). 114–114. 1 indexed citations
2.
Wilson, Lynne, Rebecca Howman, Carolyn Grove, et al.. (2024). Transcription factor 3 is dysregulated in megakaryocytes in myelofibrosis. Platelets. 35(1). 2304173–2304173. 2 indexed citations
3.
Clarke, Sarah E., et al.. (2024). Imaging flow cytometric detection of del(17p) in bone marrow and circulating plasma cells in multiple myeloma. International Journal of Laboratory Hematology. 46(3). 495–502. 1 indexed citations
4.
Fuller, Kathryn A., et al.. (2023). Morphology of myeloproliferative neoplasms. International Journal of Laboratory Hematology. 45(S2). 59–70. 6 indexed citations
6.
Erber, Wendy N., et al.. (2023). Osteohematology: To be or Notch to be. Journal of Cellular Physiology. 238(7). 1478–1491. 3 indexed citations
7.
Zini, Gina, Giuseppe d’Onofrio, Wendy N. Erber, et al.. (2021). 2021 update of the 2012 ICSH Recommendations for identification, diagnostic value, and quantitation of schistocytes: Impact and revisions. International Journal of Laboratory Hematology. 43(6). 1264–1271. 19 indexed citations
8.
Beasley, Aaron B., Timothy Isaacs, Tersia Vermeulen, et al.. (2021). Analysis of Circulating Tumour Cells in Early-Stage Uveal Melanoma: Evaluation of Tumour Marker Expression to Increase Capture. Cancers. 13(23). 5990–5990. 9 indexed citations
10.
Fuller, Kathryn A., et al.. (2020). Automated digital enumeration of plasma cells in bone marrow trephine biopsies of multiple myeloma. Journal of Clinical Pathology. 75(1). 50–57. 1 indexed citations
11.
Liang, James, Kathryn A. Fuller, Catherine Cole, et al.. (2018). Automated enumeration of lymphoid and plasma cells in bone marrow to establish normal reference ranges. Journal of Clinical Pathology. 71(10). 916–925. 7 indexed citations
12.
Isaacs, Timothy, Aaron B. Beasley, Adnan Khattak, et al.. (2017). DETECTION OF CHROMOSOMAL ABERRATIONS ASSOCIATED WITH PROGNOSIS OF UVEAL MELANOMA USING CIRCULATING TUMOUR CELLS. Clinical and Experimental Ophthalmology. 45. 61–61. 1 indexed citations
13.
Fuller, Kathryn A., et al.. (2016). TGFα expression in myeloid malignancies. Journal of Clinical Pathology. 69(6). 543–546. 5 indexed citations
14.
Kuek, Vincent, Zhifan Yang, Shek Man Chim, et al.. (2016). NPNT is Expressed by Osteoblasts and Mediates Angiogenesis via the Activation of Extracellular Signal-regulated Kinase. Scientific Reports. 6(1). 36210–36210. 24 indexed citations
15.
Fuller, Kathryn A., Jyoti Nangalia, Katie Meehan, et al.. (2015). Megakaryocytic hyperplasia in myeloproliferative neoplasms is driven by disordered proliferative, apoptotic and epigenetic mechanisms. Journal of Clinical Pathology. 69(2). 155–163. 20 indexed citations
16.
Guerrero, José A., Cavan Bennett, Louise van der Weyden, et al.. (2014). Gray platelet syndrome: proinflammatory megakaryocytes and α-granule loss cause myelofibrosis and confer metastasis resistance in mice. Blood. 124(24). 3624–3635. 61 indexed citations
17.
Zini, Gina, Giuseppe d’Onofrio, Carol Briggs, et al.. (2011). ICSH recommendations for identification, diagnostic value, and quantitation of schistocytes. International Journal of Laboratory Hematology. 34(2). 107–116. 129 indexed citations
18.
Scott, Linda M., et al.. (2007). JAK2 exon 12 mutations occur frequently in idiopathic erythrocytosis patients with low serum erythropoietin levels. Research Portal (Queen's University Belfast). 1 indexed citations
19.
Simpson, M. Cather, et al.. (1998). White cells in fresh‐frozen plasma: evaluation of a new white cell‐reduction filter. Transfusion. 38(7). 645–649. 27 indexed citations
20.
Davey, Frederick R., Wendy N. Erber, Kevin C. Gatter, & David Y. Mason. (1987). Immunophenotyping of acute myeloid leukemia by immuno‐alkaline phosphatase (APAAP) labeling with a panel of antibodies. American Journal of Hematology. 26(2). 157–166. 29 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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