Olivia Hatton

1.6k total citations · 1 hit paper
16 papers, 955 citations indexed

About

Olivia Hatton is a scholar working on Oncology, Pathology and Forensic Medicine and Immunology. According to data from OpenAlex, Olivia Hatton has authored 16 papers receiving a total of 955 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Oncology, 8 papers in Pathology and Forensic Medicine and 8 papers in Immunology. Recurrent topics in Olivia Hatton's work include Viral-associated cancers and disorders (10 papers), Lymphoma Diagnosis and Treatment (8 papers) and Immune Cell Function and Interaction (6 papers). Olivia Hatton is often cited by papers focused on Viral-associated cancers and disorders (10 papers), Lymphoma Diagnosis and Treatment (8 papers) and Immune Cell Function and Interaction (6 papers). Olivia Hatton collaborates with scholars based in United States, Italy and Sweden. Olivia Hatton's co-authors include Olivia M. Martinez, Sheri M. Krams, Allison Nau, Arnold Han, Xuhuai Ji, Alessandro Sette, Lisa E. Wagar, Florian Rubelt, Cecilia S. Lindestam Arlehamn and Scott D. Boyd and has published in prestigious journals such as Nature, Journal of Biological Chemistry and Blood.

In The Last Decade

Olivia Hatton

16 papers receiving 948 citations

Hit Papers

Identifying specificity groups in the T cell receptor rep... 2017 2026 2020 2023 2017 100 200 300 400 500
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Identifying specificity groups in the T cell receptor repertoire
    2017 595 citations Jacob Glanville, Huang Huang et al. Nature profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Olivia Hatton United States 10 593 400 313 137 116 16 955
Sibille Humme Germany 7 491 0.8× 397 1.0× 263 0.8× 186 1.4× 165 1.4× 7 959
Carine Paturel France 13 1.1k 1.8× 387 1.0× 345 1.1× 160 1.2× 103 0.9× 28 1.4k
Sonja Meixlsperger Germany 11 595 1.0× 293 0.7× 228 0.7× 100 0.7× 132 1.1× 14 918
Michelle A. Neller Australia 18 627 1.1× 490 1.2× 223 0.7× 226 1.6× 104 0.9× 33 992
Nilushi S. De Silva United States 10 1.0k 1.7× 203 0.5× 417 1.3× 114 0.8× 123 1.1× 12 1.4k
Sébastien Storck France 16 650 1.1× 125 0.3× 504 1.6× 101 0.7× 95 0.8× 19 1.2k
Sarah L. Buchan United Kingdom 18 829 1.4× 434 1.1× 392 1.3× 65 0.5× 60 0.5× 26 1.1k
Carmela La Mendola Italy 13 1.2k 2.1× 702 1.8× 167 0.5× 105 0.8× 44 0.4× 19 1.5k
Venkateswara R. Simhadri United States 18 1.1k 1.8× 349 0.9× 412 1.3× 116 0.8× 58 0.5× 21 1.4k
Hanna IJspeert Netherlands 20 637 1.1× 162 0.4× 530 1.7× 184 1.3× 44 0.4× 42 1.2k

Countries citing papers authored by Olivia Hatton

Since Specialization
Citations

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

Fields of papers citing papers by Olivia Hatton

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Olivia Hatton

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

All Works

16 of 16 papers shown
1.
Martin, E. M., et al.. (2022). An Antisense RNA Fine-Tunes Gene Expression of the Type II MazEF Toxin-Antitoxin System. mBio. 13(1). e0344321–e0344321. 3 indexed citations
2.
Smith, David W., Matteo Lunghi, Einar B. Ólafsson, et al.. (2022). A High-Throughput Amenable Dual Luciferase System for Measuring Toxoplasma gondii Bradyzoite Viability after Drug Treatment. Analytical Chemistry. 95(2). 668–676. 3 indexed citations
3.
Hatton, Olivia, et al.. (2020). Epstein–Barr virus peptides derived from latent cycle proteins alter NKG2A + NK cell effector function. Scientific Reports. 10(1). 19973–19973. 21 indexed citations
4.
Hatton, Olivia, et al.. (2020). Epstein-Barr Virus Peptides Derived from Latent Cycle Proteins Prevent the Inhibition of NKG2A Expressing NK Cells. SSRN Electronic Journal. 1 indexed citations
5.
Hatton, Olivia, et al.. (2020). Evaluating the Antiparasitic Activity of Novel BPZ Derivatives Against Toxoplasma gondii. Microorganisms. 8(8). 1159–1159. 3 indexed citations
6.
Hatton, Olivia, et al.. (2019). Epstein-Barr Virus Latent Membrane Protein 1 Regulates Host B Cell MicroRNA-155 and Its Target FOXO3a via PI3K p110α Activation. Frontiers in Microbiology. 10. 2692–2692. 9 indexed citations
7.
Glanville, Jacob, Huang Huang, Allison Nau, et al.. (2017). Identifying specificity groups in the T cell receptor repertoire. Nature. 547(7661). 94–98. 595 indexed citations breakdown →
8.
Hatton, Olivia, Dara M. Strauss‐Albee, Nancy Q. Zhao, et al.. (2016). NKG2A-Expressing Natural Killer Cells Dominate the Response to Autologous Lymphoblastoid Cells Infected with Epstein–Barr Virus. Frontiers in Immunology. 7. 607–607. 40 indexed citations
9.
Hatton, Olivia, et al.. (2014). The interplay between Epstein–Barr virus and B lymphocytes: implications for infection, immunity, and disease. Immunologic Research. 58(2-3). 268–276. 143 indexed citations
10.
Hatton, Olivia, et al.. (2014). Modulation of the B Cell MiRNome By Epstein Barr Virus.. Transplantation. 98. 240–240. 1 indexed citations
11.
Hatton, Olivia, Stacie Lambert, Maria Vaysberg, et al.. (2013). Syk-Induced Phosphatidylinositol-3-Kinase Activation in Epstein–Barr Virus Posttransplant Lymphoproliferative Disorder. American Journal of Transplantation. 13(4). 883–890. 14 indexed citations
12.
Hatton, Olivia, Olivia M. Martinez, & Carlos O. Esquivel. (2012). Emerging therapeutic strategies for Epstein–Barr virus+ post‐transplant lymphoproliferative disorder. Pediatric Transplantation. 16(3). 220–229. 16 indexed citations
13.
Hatton, Olivia, Stacie Lambert, Sheri M. Krams, & Olivia M. Martinez. (2012). Src Kinase and Syk Activation Initiate PI3K Signaling by a Chimeric Latent Membrane Protein 1 in Epstein-Barr Virus (EBV)+ B Cell Lymphomas. PLoS ONE. 7(8). e42610–e42610. 32 indexed citations
14.
15.
Vaysberg, Maria, Olivia Hatton, Stacie Lambert, et al.. (2008). Tumor-derived Variants of Epstein-Barr Virus Latent Membrane Protein 1 Induce Sustained Erk Activation and c-Fos. Journal of Biological Chemistry. 283(52). 36573–36585. 32 indexed citations
16.
Sharman, Jeff P., Jonathan M. Irish, Olivia Hatton, Olivia M. Martinez, & Ronald Levy. (2007). Syk Kinase Inhibition by R406 Inhibits BCR Mediated B Cell Proliferation and Interferes with BCR Signal Transduction in Primary Tumor Samples.. Blood. 110(11). 802–802. 2 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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