Abigail Lee

1.6k total citations
20 papers, 969 citations indexed

About

Abigail Lee is a scholar working on Pathology and Forensic Medicine, Oncology and Immunology. According to data from OpenAlex, Abigail Lee has authored 20 papers receiving a total of 969 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Pathology and Forensic Medicine, 6 papers in Oncology and 5 papers in Immunology. Recurrent topics in Abigail Lee's work include Lymphoma Diagnosis and Treatment (8 papers), CAR-T cell therapy research (5 papers) and Visual perception and processing mechanisms (3 papers). Abigail Lee is often cited by papers focused on Lymphoma Diagnosis and Treatment (8 papers), CAR-T cell therapy research (5 papers) and Visual perception and processing mechanisms (3 papers). Abigail Lee collaborates with scholars based in United Kingdom, United States and Australia. Abigail Lee's co-authors include Maria Calaminici, John G. Gribben, Andrew Clear, Janet Matthews, Jennifer Long, Blanka Golebiowski, Lisa Asper, Sameena Iqbal, Andrew Owen and Andrew Wilson and has published in prestigious journals such as Journal of Clinical Oncology, Blood and PLoS ONE.

In The Last Decade

Abigail Lee

15 papers receiving 956 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Abigail Lee United Kingdom 9 624 435 324 209 142 20 969
Johan Westerga Netherlands 11 265 0.4× 408 0.9× 132 0.4× 178 0.9× 248 1.7× 16 1.1k
Manon M. H. Huibers Netherlands 23 240 0.4× 210 0.5× 141 0.4× 154 0.7× 646 4.5× 38 1.4k
Raymond S. Lim United States 22 609 1.0× 681 1.6× 119 0.4× 160 0.8× 854 6.0× 41 2.1k
David González United Kingdom 24 806 1.3× 1.1k 2.6× 558 1.7× 259 1.2× 468 3.3× 71 2.8k
M J Cline United States 11 75 0.1× 522 1.2× 152 0.5× 189 0.9× 373 2.6× 22 1.2k
Inga Nagel Germany 20 546 0.9× 335 0.8× 322 1.0× 159 0.8× 359 2.5× 51 1.1k
C Harris United States 12 122 0.2× 635 1.5× 118 0.4× 43 0.2× 1.0k 7.2× 23 1.8k
Angelika Gutenberg Germany 21 98 0.2× 172 0.4× 231 0.7× 77 0.4× 183 1.3× 44 1.3k
A. Moseley United States 5 127 0.2× 195 0.4× 94 0.3× 155 0.7× 834 5.9× 10 1.6k
George J. Hutton United States 14 619 1.0× 188 0.4× 52 0.2× 201 1.0× 116 0.8× 46 865

Countries citing papers authored by Abigail Lee

Since Specialization
Citations

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

Fields of papers citing papers by Abigail Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Abigail Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Abigail Lee. A scholar is included among the top collaborators of Abigail Lee 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 Abigail Lee. Abigail Lee 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
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Lee, Abigail, et al.. (2024). Abstract 2628: Generation of multi-antigen specific T cells for ovarian cancer using Prussian Blue nanoparticles and photothermal therapy. Cancer Research. 84(6_Supplement). 2628–2628. 1 indexed citations
5.
Saman, Yougan, Abigail Lee, Rakesh Patel, et al.. (2023). Sex-disease dimorphism underpins enhanced motion sickness susceptibility in primary adrenal insufficiency: a cross-sectional observational study. Experimental Brain Research. 241(4). 1199–1206.
6.
Lee, Abigail, Robert S. Allison, & Laurie M. Wilcox. (2021). Depth perception from successive occlusion. Journal of Vision. 21(9). 1963–1963.
7.
Lee, Abigail, Justin M. Ales, & Julie M. Harris. (2020). Three-Dimensional Motion Perception: Comparing Speed and Speed Change Discrimination for Looming Stimuli. Vision. 4(3). 33–33. 5 indexed citations
8.
Golebiowski, Blanka, et al.. (2019). Smartphone Use and Effects on Tear Film, Blinking and Binocular Vision. Investigative Ophthalmology & Visual Science. 45(4). 428–434. 8 indexed citations
9.
Lee, Abigail, Justin M. Ales, & Julie M. Harris. (2019). Speed change discrimination for motion in depth using constant world and retinal speeds. PLoS ONE. 14(4). e0214766–e0214766. 8 indexed citations
10.
Asper, Lisa, et al.. (2019). Ocular and visual discomfort associated with smartphones, tablets and computers: what we do and do not know. Clinical and Experimental Optometry. 102(5). 463–477. 173 indexed citations
11.
Muramatsu, Masaki, Abigail Lee, Atsushi Aikawa, et al.. (2019). Transplant nephrectomy; pathological features of 124 consecutive cases in a single center study over 10 years. Journal of Nephropathology. 8(3). 23–23.
12.
Coutinho, Rita, Andrew Clear, Andrew Owen, et al.. (2013). Poor Concordance among Nine Immunohistochemistry Classifiers of Cell-of-Origin for Diffuse Large B-Cell Lymphoma: Implications for Therapeutic Strategies. Clinical Cancer Research. 19(24). 6686–6695. 83 indexed citations
13.
Kiaii, Shahryar, Andrew Clear, Alan G. Ramsay, et al.. (2013). Follicular Lymphoma Cells Induce Changes in T-Cell Gene Expression and Function: Potential Impact on Survival and Risk of Transformation. Journal of Clinical Oncology. 31(21). 2654–2661. 80 indexed citations
14.
Greaves, Paul, Andrew Clear, Andrew Owen, et al.. (2013). Defining characteristics of classical Hodgkin lymphoma microenvironment T-helper cells. Blood. 122(16). 2856–2863. 121 indexed citations
15.
Iyengar, Sunil, Andrew Clear, Csaba Bödör, et al.. (2013). P110α-mediated constitutive PI3K signaling limits the efficacy of p110δ-selective inhibition in mantle cell lymphoma, particularly with multiple relapse. Blood. 121(12). 2274–2284. 94 indexed citations
16.
Proto‐Siqueira, Rodrigo, Rodrigo Alexandre Panepucci, Abigail Lee, et al.. (2008). SAGE analysis demonstrates increased expression of TOSO contributing to Fas-mediated resistance in CLL. Blood. 112(2). 394–397. 34 indexed citations
17.
Jong, Daphne de, Andreas Rosenwald, Mukesh Chhanabhai, et al.. (2007). Immunohistochemical Prognostic Markers in Diffuse Large B-Cell Lymphoma: Validation of Tissue Microarray As a Prerequisite for Broad Clinical Applications—A Study From the Lunenburg Lymphoma Biomarker Consortium. Journal of Clinical Oncology. 25(7). 805–812. 233 indexed citations
18.
Davies, Andrew, Andreas Rosenwald, George W. Wright, et al.. (2006). Transformation of follicular lymphoma to diffuse large B‐cell lymphoma proceeds by distinct oncogenic mechanisms. British Journal of Haematology. 136(2). 286–293. 115 indexed citations
19.
Berney, Daniel M., Abigail Lee, Jonathan Shamash, & R. Timothy D. Oliver. (2005). The Frequency and Distribution of Intratubular Trophoblast in Association With Germ Cell Tumors of the Testis. The American Journal of Surgical Pathology. 29(10). 1300–1303. 12 indexed citations
20.
Lee, Abigail, Andrew Davies, Andrew Clear, et al.. (2004). Tissue Microarray Is a Useful Tool in the Evaluation of Genes Implicated in Transformation of Follicular Lymphoma.. Blood. 104(11). 2267–2267. 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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