Laura N Eadie

794 total citations
37 papers, 541 citations indexed

About

Laura N Eadie is a scholar working on Hematology, Genetics and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Laura N Eadie has authored 37 papers receiving a total of 541 indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Hematology, 16 papers in Genetics and 14 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Laura N Eadie's work include Chronic Myeloid Leukemia Treatments (25 papers), Acute Lymphoblastic Leukemia research (14 papers) and Chronic Lymphocytic Leukemia Research (13 papers). Laura N Eadie is often cited by papers focused on Chronic Myeloid Leukemia Treatments (25 papers), Acute Lymphoblastic Leukemia research (14 papers) and Chronic Lymphocytic Leukemia Research (13 papers). Laura N Eadie collaborates with scholars based in Australia, Italy and South Korea. Laura N Eadie's co-authors include Deborah L. White, Timothy P. Hughes, Verity A Saunders, David T Yeung, Phuong Dang, Amity Frede, Devendra Hiwase, Stephanie Zrim, L.B. To and D. Hewett and has published in prestigious journals such as Blood, PLoS ONE and Macromolecules.

In The Last Decade

Laura N Eadie

34 papers receiving 532 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Laura N Eadie Australia 12 381 249 177 119 110 37 541
Claudine Chollet France 6 401 1.1× 315 1.3× 134 0.8× 116 1.0× 41 0.4× 10 547
Fabio P S Santos United States 10 374 1.0× 203 0.8× 99 0.6× 171 1.4× 90 0.8× 16 520
Lisa Hopcroft United Kingdom 13 489 1.3× 293 1.2× 141 0.8× 342 2.9× 48 0.4× 23 814
Toshiya Yokozawa Japan 8 222 0.6× 107 0.4× 100 0.6× 281 2.4× 108 1.0× 17 528
Barbara Scappini Italy 15 395 1.0× 242 1.0× 110 0.6× 187 1.6× 54 0.5× 42 578
Sabine Fajmann Austria 7 288 0.8× 197 0.8× 182 1.0× 168 1.4× 51 0.5× 8 481
M Beran United States 14 407 1.1× 302 1.2× 209 1.2× 335 2.8× 155 1.4× 18 812
J. Chabrol France 5 605 1.6× 432 1.7× 137 0.8× 182 1.5× 93 0.8× 5 758
Koshi Akahane Japan 14 181 0.5× 94 0.4× 217 1.2× 301 2.5× 138 1.3× 63 658

Countries citing papers authored by Laura N Eadie

Since Specialization
Citations

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

Fields of papers citing papers by Laura N Eadie

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Laura N Eadie

This figure shows the co-authorship network connecting the top 25 collaborators of Laura N Eadie. A scholar is included among the top collaborators of Laura N Eadie 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 Laura N Eadie. Laura N Eadie 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.
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Bruning, John B., Laura N Eadie, Susan L. Heatley, et al.. (2025). Activity of STAMP inhibitors in ABL2 rearranged acute lymphoblastic leukemia is dependent on the Abl2 SH3 domain. PubMed. 2(3). 100109–100109.
3.
Yeung, David T, Laura N Eadie, Susan L. Heatley, et al.. (2024). Diagnostic genomic analysis is prognostic in AYA patients with ALL treated on an MRD-stratified pediatric protocol. PubMed. 2(1). 100041–100041. 1 indexed citations
4.
Eadie, Laura N, James Breen, Michael Osborn, et al.. (2023). Case Report: Rare IKZF1 Gene Fusions Identified in Neonate with Congenital KMT2A-Rearranged Acute Lymphoblastic Leukemia. Genes. 14(2). 264–264. 1 indexed citations
5.
Eadie, Laura N, Susan L. Heatley, Monika Kutyna, et al.. (2023). Case report: Rare case of donor cell‐derived T‐cell acute lymphoblastic leukaemia in a female patient after receiving an allo‐transplant from her male sibling. British Journal of Haematology. 203(2). 282–287. 1 indexed citations
6.
Heatley, Susan L., Laura N Eadie, Barbara J. McClure, et al.. (2023). Reproducible Bioinformatics Analysis Workflows for Detecting IGH Gene Fusions in B-Cell Acute Lymphoblastic Leukaemia Patients. Cancers. 15(19). 4731–4731. 5 indexed citations
7.
Mayoh, Chelsea, Susan L. Heatley, Barbara J. McClure, et al.. (2022). RaScALL: Rapid (Ra) screening (Sc) of RNA-seq data for prognostically significant genomic alterations in acute lymphoblastic leukaemia (ALL). PLoS Genetics. 18(10). e1010300–e1010300. 14 indexed citations
8.
Heatley, Susan L., Tamara Leclercq, Barbara J. McClure, et al.. (2021). In-vitromodeling of TKI resistance in the high-risk B-cell acute lymphoblastic leukemia fusion geneRANBP2-ABL1- implications for targeted therapy. Leukemia & lymphoma. 62(5). 1157–1166. 3 indexed citations
9.
Heatley, Susan L., Laura N Eadie, Barbara J. McClure, et al.. (2021). HMGN1 plays a significant role in CRLF2 driven Down Syndrome leukemia and provides a potential therapeutic target in this high-risk cohort. Oncogene. 41(6). 797–808. 14 indexed citations
10.
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Eadie, Laura N, et al.. (2021). Constitutive JAK/STAT signaling is the primary mechanism of resistance to JAKi in TYK2-rearranged acute lymphoblastic leukemia. Cancer Letters. 512. 28–37. 10 indexed citations
12.
McClure, Barbara J., et al.. (2020). MLLT10 rearranged acute leukemia: Incidence, prognosis, and possible therapeutic strategies. Genes Chromosomes and Cancer. 59(12). 709–721. 9 indexed citations
13.
Eadie, Laura N, Susan L. Heatley, Barbara J. McClure, et al.. (2020). Next Generation Genomic Analyses in T-ALL Patients Identify Recurrent and Novel Genomic Abnormalities. Blood. 136(Supplement 1). 13–14. 1 indexed citations
14.
McClure, Barbara J., et al.. (2019). KMT2A rearranged acute lymphoblastic leukaemia: Unravelling the genomic complexity and heterogeneity of this high-risk disease. Cancer Letters. 469. 410–418. 31 indexed citations
15.
Eadie, Laura N, Phuong Dang, Jarrad M. Goyne, Timothy P. Hughes, & Deborah L. White. (2018). ABCC6 plays a significant role in the transport of nilotinib and dasatinib, and contributes to TKI resistance in vitro, in both cell lines and primary patient mononuclear cells. PLoS ONE. 13(1). e0192180–e0192180. 20 indexed citations
16.
Eadie, Laura N, Timothy P. Hughes, & Deborah L. White. (2018). Patients with low OCT-1 activity and high ABCB1 fold rise have poor long-term outcomes in response to tyrosine kinase inhibitor therapy. Leukemia. 32(10). 2288–2291. 8 indexed citations
17.
Saunders, Verity A, Lu Liu, Laura N Eadie, et al.. (2016). A Low Concentration of ABL001 Potentiates In Vitro TKI-Induced Bcr-Abl Kinase Inhibition in CML Cells. Blood. 128(22). 1121–1121. 2 indexed citations
18.
Eadie, Laura N, Timothy P. Hughes, & Deborah L. White. (2013). Interaction of the Efflux Transporters ABCB1 and ABCG2 With Imatinib, Nilotinib, and Dasatinib. Clinical Pharmacology & Therapeutics. 95(3). 294–306. 69 indexed citations
19.
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Hiwase, Devendra, Verity A Saunders, D. Hewett, et al.. (2008). Dasatinib Cellular Uptake and Efflux in Chronic Myeloid Leukemia Cells: Therapeutic Implications. Clinical Cancer Research. 14(12). 3881–3888. 154 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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