Nicola Long

2.7k total citations
17 papers, 203 citations indexed

About

Nicola Long is a scholar working on Hematology, Molecular Biology and Genetics. According to data from OpenAlex, Nicola Long has authored 17 papers receiving a total of 203 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Hematology, 7 papers in Molecular Biology and 4 papers in Genetics. Recurrent topics in Nicola Long's work include Acute Myeloid Leukemia Research (15 papers), Chronic Myeloid Leukemia Treatments (5 papers) and Chronic Lymphocytic Leukemia Research (2 papers). Nicola Long is often cited by papers focused on Acute Myeloid Leukemia Research (15 papers), Chronic Myeloid Leukemia Treatments (5 papers) and Chronic Lymphocytic Leukemia Research (2 papers). Nicola Long collaborates with scholars based in United States, India and Switzerland. Nicola Long's co-authors include Jeffrey Tyner, Shannon K. McWeeney, Anupriya Agarwal, Andy Kaempf, Motomi Mori, Brian Druker, David K. Edwards, Alisa Damnernsawad, Adam J. Lamble and Kevin Watanabe‐Smith and has published in prestigious journals such as Blood, Frontiers in Immunology and British Journal of Haematology.

In The Last Decade

Nicola Long

14 papers receiving 201 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nicola Long United States 7 119 85 54 48 32 17 203
Peter Tan Australia 10 126 1.1× 109 1.3× 85 1.6× 33 0.7× 55 1.7× 18 252
Shawn Sarkaria United States 6 103 0.9× 164 1.9× 24 0.4× 55 1.1× 37 1.2× 9 239
Corinna Albers Germany 7 89 0.7× 92 1.1× 23 0.4× 42 0.9× 25 0.8× 13 171
Galina Tsykunova Norway 8 147 1.2× 103 1.2× 21 0.4× 25 0.5× 30 0.9× 25 200
Vijitha Sathiaseelan United Kingdom 5 133 1.1× 134 1.6× 24 0.4× 54 1.1× 22 0.7× 7 198
Sanchari Bhattacharyya United States 2 113 0.9× 67 0.8× 72 1.3× 29 0.6× 44 1.4× 3 176
Ying‐Jung Huang Taiwan 9 172 1.4× 134 1.6× 24 0.4× 70 1.5× 26 0.8× 21 243
Sivahari Prasad Gorantla Germany 7 83 0.7× 70 0.8× 26 0.5× 54 1.1× 41 1.3× 24 162
Seo-Yeon Ahn South Korea 7 123 1.0× 51 0.6× 65 1.2× 47 1.0× 73 2.3× 26 215
Marco De Dominici United States 10 107 0.9× 188 2.2× 50 0.9× 43 0.9× 84 2.6× 17 293

Countries citing papers authored by Nicola Long

Since Specialization
Citations

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

Fields of papers citing papers by Nicola Long

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nicola Long

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

All Works

17 of 17 papers shown
1.
Eide, Christopher A., Stephen E. Kurtz, Nicola Long, et al.. (2026). DDX41-Mutated AML: A Case Report and Perspectives. JCO Precision Oncology. 10(1). e2500992–e2500992.
2.
Eide, Christopher A., Stephen E. Kurtz, Andy Kaempf, et al.. (2025). A rapid gene expression profiler predicts tumor responsiveness and patient outcome for standard-of-care therapies in acute myeloid leukemia. Blood. 146(Supplement 1). 657–657.
3.
Flynn, Patrick, Mark D. Long, Yoko Kosaka, et al.. (2024). Leukemic mutation FLT3-ITD is retained in dendritic cells and disrupts their homeostasis leading to expanded Th17 frequency. Frontiers in Immunology. 15. 1297338–1297338. 4 indexed citations
4.
Stewart, Melissa L., Daniel Bottomly, Andy Kaempf, et al.. (2024). Combination with Palbociclib Overcomes Venetoclax Resistance Mechanisms and Outperforms Single Agent Efficacy in Acute Myeloid Leukemia. Blood. 144(Supplement 1). 1566–1566. 1 indexed citations
5.
Li, Peng, Philipp W. Raess, Jennifer Dunlap, et al.. (2024). Landscape of somatic mutations and clonal evolution in NUP98‐rearranged adult acute myeloid leukaemia. British Journal of Haematology. 206(4). 1097–1102. 1 indexed citations
6.
Li, Yonghong, Fei Yang, Nicola Long, et al.. (2023). NGS-defined measurable residual disease (MRD) after initial chemotherapy as a prognostic biomarker for acute myeloid leukemia. Blood Cancer Journal. 13(1). 12 indexed citations
7.
Coleman, Daniel J., Joseph Estabrook, Emek Demir, et al.. (2023). Disruption of the MYC Superenhancer Complex by Dual Targeting of FLT3 and LSD1 in Acute Myeloid Leukemia. Molecular Cancer Research. 21(7). 631–647. 5 indexed citations
8.
Romine, Kyle A., et al.. (2023). Immune cell proportions correlate with clinicogenomic features and ex vivo drug responses in acute myeloid leukemia. Frontiers in Oncology. 13. 1192829–1192829. 1 indexed citations
9.
Eide, Christopher A., Stephen E. Kurtz, Andy Kaempf, et al.. (2023). Clinical Correlates of Venetoclax-Based Combination Sensitivities to Augment Acute Myeloid Leukemia Therapy. Blood Cancer Discovery. 4(6). 452–467. 12 indexed citations
10.
Kurtz, Stephen E., Christopher A. Eide, Andy Kaempf, et al.. (2022). Associating drug sensitivity with differentiation status identifies effective combinations for acute myeloid leukemia. Blood Advances. 6(10). 3062–3067. 6 indexed citations
11.
Eide, Christopher A., Stephen E. Kurtz, Andy Kaempf, et al.. (2022). Defining Clinical and Molecular Biomarkers for Venetoclax-Based Drug Combinations to Augment AML Therapy. Blood. 140(Supplement 1). 1025–1027. 1 indexed citations
12.
Lachowiez, Curtis A., Nicola Long, Jennifer N. Saultz, et al.. (2022). Comparison and validation of the 2022 European LeukemiaNet guidelines in acute myeloid leukemia. Blood Advances. 7(9). 1899–1909. 43 indexed citations
13.
Eide, Christopher A., Stephen E. Kurtz, Andy Kaempf, et al.. (2020). Simultaneous kinase inhibition with ibrutinib and BCL2 inhibition with venetoclax offers a therapeutic strategy for acute myeloid leukemia. Leukemia. 34(9). 2342–2353. 16 indexed citations
14.
Eide, Christopher A., Stephen E. Kurtz, Andy Kaempf, et al.. (2019). Simultaneous Kinase Inhibition with Ibrutinib and BCL2 Inhibition with Venetoclax As a Therapeutic Strategy for Acute Lymphoblastic Leukemia. Blood. 134(Supplement_1). 3950–3950.
15.
Kurtz, Stephen E., Christopher A. Eide, Andy Kaempf, et al.. (2019). Patterns of Sensitivity Exhibited By Venetoclax-Inclusive Drug Combinations in Acute Myeloid Leukemia. Blood. 134(Supplement_1). 878–878. 2 indexed citations
16.
Zhang, Haijiao, Stephen Moore, Susan B. Olson, et al.. (2018). Two myeloid leukemia cases with rare FLT3 fusions. Molecular Case Studies. 4(6). a003079–a003079. 17 indexed citations
17.
Edwards, David K., Kevin Watanabe‐Smith, Angela Rofelty, et al.. (2018). CSF1R inhibitors exhibit antitumor activity in acute myeloid leukemia by blocking paracrine signals from support cells. Blood. 133(6). 588–599. 82 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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