Matthew Gumbleton

1.4k total citations
9 papers, 209 citations indexed

About

Matthew Gumbleton is a scholar working on Immunology, Hematology and Molecular Biology. According to data from OpenAlex, Matthew Gumbleton has authored 9 papers receiving a total of 209 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Immunology, 3 papers in Hematology and 2 papers in Molecular Biology. Recurrent topics in Matthew Gumbleton's work include Immune Cell Function and Interaction (5 papers), T-cell and B-cell Immunology (3 papers) and Hematopoietic Stem Cell Transplantation (2 papers). Matthew Gumbleton is often cited by papers focused on Immune Cell Function and Interaction (5 papers), T-cell and B-cell Immunology (3 papers) and Hematopoietic Stem Cell Transplantation (2 papers). Matthew Gumbleton collaborates with scholars based in United States, France and Netherlands. Matthew Gumbleton's co-authors include William G. Kerr, John D. Chisholm, Robert W. Brooks, Sonia Iyer, Éric Vivier, Bonnie B. Toms, Gwenny M. Fuhler, Christopher M. Russo, Sandra Fernandes and Raki Sudan and has published in prestigious journals such as The Journal of Immunology, Frontiers in Immunology and Molecular Cancer Therapeutics.

In The Last Decade

Matthew Gumbleton

7 papers receiving 206 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Matthew Gumbleton United States	6	119	97	41	21	19	9	209
Tina M. Schnöder Germany	10	112 0.9×	55 0.6×	29 0.7×	31 1.5×	42 2.2×	14	200
Hualong Yan United States	8	175 1.5×	52 0.5×	68 1.7×	10 0.5×	10 0.5×	13	228
Andrew Nickless United States	6	222 1.9×	52 0.5×	28 0.7×	18 0.9×	12 0.6×	9	281
Joanna Fares France	8	137 1.2×	41 0.4×	32 0.8×	27 1.3×	10 0.5×	12	205
Waruni Abeysekera Australia	7	181 1.5×	108 1.1×	63 1.5×	23 1.1×	5 0.3×	11	291
Giacomo Volpe United Kingdom	11	191 1.6×	39 0.4×	29 0.7×	11 0.5×	26 1.4×	23	273
Ana Krolo Austria	7	62 0.5×	69 0.7×	16 0.4×	9 0.4×	20 1.1×	11	143
Nuno Saraiva-Agostinho Portugal	4	203 1.7×	22 0.2×	37 0.9×	9 0.4×	8 0.4×	8	252
Anna Ringler Austria	5	136 1.1×	29 0.3×	38 0.9×	10 0.5×	9 0.5×	5	185
Jacob V. Layer United States	7	100 0.8×	23 0.2×	40 1.0×	24 1.1×	16 0.8×	11	176

Countries citing papers authored by Matthew Gumbleton

Since Specialization

Citations

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

Fields of papers citing papers by Matthew Gumbleton

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthew Gumbleton

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

All Works

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9 of 9 papers shown

Jo, Yeonjung, Sonam Puri, Benjamin Haaland, et al.. (2024). Augmenting Prognostication: Utilizing Activity Trackers to Enhance Survival Prediction in Metastatic Non-Small Cell Lung Cancer. Clinical Lung Cancer. 26(1). 29–38.

Bowen, Anneli R., et al.. (2024). Lichen striatus as an immune-related adverse event following ipilimumab/nivolumab and COVID-19 infection in an adult. JAAD Case Reports. 52. 34–37.

Gumbleton, Matthew, Raki Sudan, Sandra Fernandes, et al.. (2017). Dual enhancement of T and NK cell function by pulsatile inhibition of SHIP1 improves antitumor immunity and survival. Science Signaling. 10(500). 31 indexed citations

Fernandes, Sandra, Robert W. Brooks, Matthew Gumbleton, et al.. (2015). SHIPi Enhances Autologous and Allogeneic Hematopoietic Stem Cell Transplantation. EBioMedicine. 2(3). 205–213. 14 indexed citations

Gumbleton, Matthew, Éric Vivier, & William G. Kerr. (2015). SHIP1 Intrinsically Regulates NK Cell Signaling and Education, Resulting in Tolerance of an MHC Class I–Mismatched Bone Marrow Graft in Mice. The Journal of Immunology. 194(6). 2847–2854. 29 indexed citations

Iyer, Sonia, Robert W. Brooks, Matthew Gumbleton, & William G. Kerr. (2014). SHIP1-Expressing Mesenchymal Stem Cells Regulate Hematopoietic Stem Cell Homeostasis and Lineage Commitment During Aging. Stem Cells and Development. 24(9). 1073–1081. 16 indexed citations

Gumbleton, Matthew & William G. Kerr. (2013). Role of inositol phospholipid signaling in natural killer cell biology. Frontiers in Immunology. 4. 47–47. 26 indexed citations

Fuhler, Gwenny M., Robert W. Brooks, Bonnie B. Toms, et al.. (2011). Therapeutic Potential of SH2 Domain-Containing Inositol-5′-Phosphatase 1 (SHIP1) and SHIP2 Inhibition in Cancer. Molecular Medicine. 18(1). 65–75. 91 indexed citations

Kerr, William G., Robert W. Brooks, Mi-Young Park, et al.. (2011). Abstract C81: Therapeutic potential of SHIP1 and SHIP2 inhibitors in cancer.. Molecular Cancer Therapeutics. 10(11_Supplement). C81–C81. 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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