Geoffrey Neale

24.3k total citations · 7 hit papers
171 papers, 15.3k citations indexed

About

Geoffrey Neale is a scholar working on Molecular Biology, Immunology and Oncology. According to data from OpenAlex, Geoffrey Neale has authored 171 papers receiving a total of 15.3k indexed citations (citations by other indexed papers that have themselves been cited), including 79 papers in Molecular Biology, 62 papers in Immunology and 27 papers in Oncology. Recurrent topics in Geoffrey Neale's work include Immune Cell Function and Interaction (37 papers), T-cell and B-cell Immunology (27 papers) and Acute Myeloid Leukemia Research (18 papers). Geoffrey Neale is often cited by papers focused on Immune Cell Function and Interaction (37 papers), T-cell and B-cell Immunology (27 papers) and Acute Myeloid Leukemia Research (18 papers). Geoffrey Neale collaborates with scholars based in United States, Japan and United Kingdom. Geoffrey Neale's co-authors include Peter Vogel, Hongbo Chi, Thirumala‐Devi Kanneganti, Douglas R. Green, Kai Yang, R. K. Subbarao Malireddi, Rajendra Karki, Gonghua Huang, Lewis Z. Shi and Ruoning Wang and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Geoffrey Neale

167 papers receiving 15.2k citations

Hit Papers

5 papers align trajectories

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.

HIF1α–dependent glycolytic pathway orchestrates a metabolic checkpoint for the differentiation of TH17 and Treg cells

2011 1.4k citations Peter Vogel, Geoffrey Neale et al. profile →
Synergism of TNF-α and IFN-γ Triggers Inflammatory Cell Death, Tissue Damage, and Mortality in SARS-CoV-2 Infection and Cytokine Shock Syndromes

2020 1.1k citations Rajendra Karki, Bhesh Raj Sharma et al. profile →
mTORC1 couples immune signals and metabolic programming to establish Treg-cell function

2013 614 citations Hu Zeng, Kai Yang et al. profile →
ZBP1/DAI is an innate sensor of influenza virus triggering the NLRP3 inflammasome and programmed cell death pathways

2016 613 citations R. K. Subbarao Malireddi, Rajendra Karki et al. Science Immunology profile →
Inflammasome is a central player in the induction of obesity and insulin resistance

2011 605 citations Rinke Stienstra, Janna A. van Diepen et al. Proceedings of the National Academy of Sciences profile →
De Novo Epigenetic Programs Inhibit PD-1 Blockade-Mediated T Cell Rejuvenation

2017 567 citations Yiping Fan, Pradyot Dash et al. profile →
ADAR1 restricts ZBP1-mediated immune response and PANoptosis to promote tumorigenesis

2021 298 citations Rajendra Karki, Balamurugan Sundaram et al. Cell Reports profile →

Peers

Geoffrey Neale

IMMUN

ONCOL

EPIDE

Philippe Bouillet Australia

Fabienne Mackay Australia

Jonathan D. Powell United States

Clifford A. Lowell United States

Paul J. Coffer Netherlands

Robert P. Kimberly United States

S J Korsmeyer United States

Kazuo Sugamura Japan

George C. Tsokos United States

Leonidas C. Platanias United States

Philippe Bouillet Australia

Geoffrey Neale

10.7k ×1.5

5.6k ×0.8

IMMUN

3.1k ×1.3

ONCOL

1.9k ×1.0

EPIDE

1.5k ×0.9

Citations per year, relative to Geoffrey Neale Geoffrey Neale (= 1×) peers Philippe Bouillet

Countries citing papers authored by Geoffrey Neale

Since Specialization

Citations

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

Fields of papers citing papers by Geoffrey Neale

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Geoffrey Neale

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Fukuda, Yu, John P. Lynch, Abhijat Sheth, et al.. (2025). Somatic mtDNA mutation burden shapes metabolic plasticity in leukemogenesis. Science Advances. 11(1). eads8489–eads8489.

Tartey, Sarang, Geoffrey Neale, Peter Vogel, R. K. Subbarao Malireddi, & Thirumala‐Devi Kanneganti. (2021). A MyD88/IL1R Axis Regulates PD-1 Expression on Tumor-Associated Macrophages and Sustains Their Immunosuppressive Function in Melanoma. Cancer Research. 81(9). 2358–2372. 23 indexed citations

Karki, Rajendra, Balamurugan Sundaram, Bhesh Raj Sharma, et al.. (2021). ADAR1 restricts ZBP1-mediated immune response and PANoptosis to promote tumorigenesis. Cell Reports. 37(3). 109858–109858. 298 indexed citations breakdown →

Jeffers, John, Emília M. Pinto, Jerold E. Rehg, et al.. (2021). The Common Germline TP53-R337H Mutation Is Hypomorphic and Confers Incomplete Penetrance and Late Tumor Onset in a Mouse Model. Cancer Research. 81(9). 2442–2456. 9 indexed citations

Klein, Jonathon, Yumei Zheng, Travis Eisemann, et al.. (2020). Tissue-Specific Regulation of the Wnt/β-Catenin Pathway by PAGE4 Inhibition of Tankyrase. Cell Reports. 32(3). 107922–107922. 10 indexed citations

Saravia, Jordy, Hu Zeng, Yogesh Dhungana, et al.. (2020). Homeostasis and transitional activation of regulatory T cells require c-Myc. Science Advances. 6(1). eaaw6443–eaaw6443. 60 indexed citations

Wang, Yanyan, Xingrong Du, Jun Wei, et al.. (2019). LKB1 orchestrates dendritic cell metabolic quiescence and anti-tumor immunity. Cell Research. 29(5). 391–405. 53 indexed citations

Yang, Kai, Daniel Bastardo Blanco, Xiang Chen, et al.. (2018). Metabolic signaling directs the reciprocal lineage decisions of αβ and γδ T cells. Science Immunology. 3(25). 62 indexed citations

Shi, Hao, Haiyan Tan, Yuxin Li, et al.. (2018). Hippo Kinases Mst1 and Mst2 Sense and Amplify IL-2R-STAT5 Signaling in Regulatory T Cells to Establish Stable Regulatory Activity. Immunity. 49(5). 899–914.e6. 87 indexed citations

10.

Pinto, Emília M., Carlos Rodríguez‐Galindo, John Choi, et al.. (2016). Prognostic Significance of Major Histocompatibility Complex Class II Expression in Pediatric Adrenocortical Tumors: A St. Jude and Children's Oncology Group Study. Clinical Cancer Research. 22(24). 6247–6255. 24 indexed citations

11.

Jones, Bart G., Rhiannon R. Penkert, Beisi Xu, et al.. (2016). Binding of estrogen receptors to switch sites and regulatory elements in the immunoglobulin heavy chain locus of activated B cells suggests a direct influence of estrogen on antibody expression. Molecular Immunology. 77. 97–102. 38 indexed citations

12.

Baker, Sharyn D., Eric I. Zimmerman, Yong‐Dong Wang, et al.. (2013). Emergence of Polyclonal FLT3 Tyrosine Kinase Domain Mutations during Sequential Therapy with Sorafenib and Sunitinib in FLT3-ITD–Positive Acute Myeloid Leukemia. Clinical Cancer Research. 19(20). 5758–5768. 75 indexed citations

13.

Stienstra, Rinke, Janna A. van Diepen, Cees J. Tack, et al.. (2011). Inflammasome is a central player in the induction of obesity and insulin resistance. Proceedings of the National Academy of Sciences. 108(37). 15324–15329. 605 indexed citations breakdown →

14.

Kawedia, Jitesh D., Sue C. Kaste, Deqing Pei, et al.. (2010). Pharmacokinetic, pharmacodynamic, and pharmacogenetic determinants of osteonecrosis in children with acute lymphoblastic leukemia. Blood. 117(8). 2340–2347. 186 indexed citations

15.

Stow, Patricia, Laura Key, Xiaohua Chen, et al.. (2010). Clinical significance of low levels of minimal residual disease at the end of remission induction therapy in childhood acute lymphoblastic leukemia. Blood. 115(23). 4657–4663. 103 indexed citations

16.

Saab, Raya, Carlos Rodríguez‐Galindo, Jerold E. Rehg, et al.. (2009). p18Ink4c and p53 Act as Tumor Suppressors in Cyclin D1 –Driven Primitive Neuroectodermal Tumor. Cancer Research. 69(2). 440–448. 17 indexed citations

17.

Neale, Geoffrey, Xiaoping Su, Christopher L. Morton, et al.. (2008). Molecular Characterization of the Pediatric Preclinical Testing Panel. Clinical Cancer Research. 14(14). 4572–4583. 95 indexed citations

18.

West, Alina Nico, Geoffrey Neale, Stanley Pounds, et al.. (2007). Gene Expression Profiling of Childhood Adrenocortical Tumors. Cancer Research. 67(2). 600–608. 116 indexed citations

19.

Fujii, Naoaki, Liang You, Zhidong Xu, et al.. (2007). An Antagonist of Dishevelled Protein-Protein Interaction Suppresses β-Catenin–Dependent Tumor Cell Growth. Cancer Research. 67(2). 573–579. 187 indexed citations

20.

Armstrong, Joshua, et al.. (1991). Artificial nutrition support for patients in the Cambridge Health District.. PubMed. 23(3). 93–100. 12 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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