Tom O’Toole

2.0k total citations
19 papers, 1.1k citations indexed

About

Tom O’Toole is a scholar working on Immunology, Molecular Biology and Surgery. According to data from OpenAlex, Tom O’Toole has authored 19 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Immunology, 9 papers in Molecular Biology and 1 paper in Surgery. Recurrent topics in Tom O’Toole's work include Immunotherapy and Immune Responses (11 papers), Immune Cell Function and Interaction (10 papers) and T-cell and B-cell Immunology (5 papers). Tom O’Toole is often cited by papers focused on Immunotherapy and Immune Responses (11 papers), Immune Cell Function and Interaction (10 papers) and T-cell and B-cell Immunology (5 papers). Tom O’Toole collaborates with scholars based in Netherlands, United States and Germany. Tom O’Toole's co-authors include Reina E. Mebius, Rosalie Molenaar, Mascha Greuter, Georg Kraal, Maikel P. Peppelenbosch, Frank J. Bruggeman, Bas Teusink, Johan H. van Heerden, Marjolein van Egmond and Rens Braster and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

In The Last Decade

Tom O’Toole

19 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tom O’Toole Netherlands 16 558 529 120 75 69 19 1.1k
Zhiqiang Han China 15 729 1.3× 415 0.8× 228 1.9× 31 0.4× 57 0.8× 33 1.4k
Masataka Horiuchi Japan 19 689 1.2× 550 1.0× 145 1.2× 66 0.9× 89 1.3× 32 1.4k
Cesar F. Ortega-Cava Japan 15 434 0.8× 403 0.8× 179 1.5× 47 0.6× 83 1.2× 19 1.1k
Myung Kyu Lee South Korea 20 892 1.6× 140 0.3× 147 1.2× 59 0.8× 66 1.0× 49 1.4k
Alexandre Fontayne France 18 536 1.0× 418 0.8× 48 0.4× 197 2.6× 55 0.8× 28 1.2k
Vanesa G. Martínez Spain 16 639 1.1× 267 0.5× 174 1.4× 22 0.3× 51 0.7× 21 1.1k
Marie-Ève Paquet Canada 16 593 1.1× 570 1.1× 62 0.5× 36 0.5× 143 2.1× 22 1.3k
Julia Heinrich United States 16 664 1.2× 297 0.6× 128 1.1× 258 3.4× 40 0.6× 32 1.1k
Wenjie Zhai China 21 645 1.2× 541 1.0× 461 3.8× 95 1.3× 111 1.6× 42 1.5k
Jacques Bartholeyns France 21 632 1.1× 663 1.3× 274 2.3× 88 1.2× 50 0.7× 61 1.3k

Countries citing papers authored by Tom O’Toole

Since Specialization
Citations

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

Fields of papers citing papers by Tom O’Toole

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tom O’Toole. 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 Tom O’Toole. The network helps show where Tom O’Toole may publish in the future.

Co-authorship network of co-authors of Tom O’Toole

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

All Works

19 of 19 papers shown
1.
Fens, Marcel H.A.M., Ryan Nelson, Anja Krippner‐Heidenreich, et al.. (2023). Increased Bone Marrow Uptake and Accumulation of Very-Late Antigen-4 Targeted Lipid Nanoparticles. Pharmaceutics. 15(6). 1603–1603. 16 indexed citations
2.
Botman, Dennis, Tom O’Toole, Joachim Goedhart, et al.. (2021). A yeast FRET biosensor enlightens cAMP signaling. Molecular Biology of the Cell. 32(13). 1229–1240. 15 indexed citations
3.
Cornelissen, Lenneke A. M., Athanasios Blanas, Joost C. van der Horst, et al.. (2020). Tn Antigen Expression Contributes to an Immune Suppressive Microenvironment and Drives Tumor Growth in Colorectal Cancer. Frontiers in Oncology. 10. 1622–1622. 45 indexed citations
4.
Fehres, Cynthia M., Lisa G. M. van Baarsen, N. van Uden, et al.. (2019). BOB.1 controls memory B-cell fate in the germinal center reaction. Journal of Autoimmunity. 101. 131–144. 11 indexed citations
5.
Cornelissen, Lenneke A. M., Athanasios Blanas, Joost C. van der Horst, et al.. (2018). Disruption of sialic acid metabolism drives tumor growth by augmenting CD8+ T cell apoptosis. International Journal of Cancer. 144(9). 2290–2302. 37 indexed citations
6.
Pinheiro, Melissa A Lopes, Alwin Kamermans, Juan J. García‐Vallejo, et al.. (2016). Internalization and presentation of myelin antigens by the brain endothelium guides antigen-specific T cell migration. eLife. 5. 44 indexed citations
7.
Koning, Jasper J., Tanja Konijn, Kim Lakeman, et al.. (2016). Nestin-Expressing Precursors Give Rise to Both Endothelial as well as Nonendothelial Lymph Node Stromal Cells. The Journal of Immunology. 197(7). 2686–2694. 25 indexed citations
8.
Ruben, Jurjen M., Lindy L. Visser, Kimberley M. Heinhuis, et al.. (2015). A Human Cell Line Model for Interferon-α Driven Dendritic Cell Differentiation. PLoS ONE. 10(8). e0135219–e0135219. 3 indexed citations
10.
Heerden, Johan H. van, Meike T. Wortel, Frank J. Bruggeman, et al.. (2014). Lost in Transition: Start-Up of Glycolysis Yields Subpopulations of Nongrowing Cells. Science. 343(6174). 1245114–1245114. 215 indexed citations
11.
Schneiders, Famke L., Jurjen M. Ruben, Tom O’Toole, et al.. (2014). CD1d-Restricted Antigen Presentation by Vγ9Vδ2-T Cells Requires Trogocytosis. Cancer Immunology Research. 2(8). 732–740. 18 indexed citations
12.
Braster, Rens, Tom O’Toole, & Marjolein van Egmond. (2013). Myeloid cells as effector cells for monoclonal antibody therapy of cancer. Methods. 65(1). 28–37. 68 indexed citations
13.
Molenaar, Rosalie, Marlene Knippenberg, Gera Goverse, et al.. (2011). Expression of Retinaldehyde Dehydrogenase Enzymes in Mucosal Dendritic Cells and Gut-Draining Lymph Node Stromal Cells Is Controlled by Dietary Vitamin A. The Journal of Immunology. 186(4). 1934–1942. 139 indexed citations
14.
Molenaar, Rosalie, Mascha Greuter, Ramon Roozendaal, et al.. (2009). Lymph Node Stromal Cells Support Dendritic Cell-Induced Gut-Homing of T Cells. The Journal of Immunology. 183(10). 6395–6402. 108 indexed citations
15.
Backer, Ronald A., Timo Schwandt, Mascha Greuter, et al.. (2009). Effective collaboration between marginal metallophilic macrophages and CD8+dendritic cells in the generation of cytotoxic T cells. Proceedings of the National Academy of Sciences. 107(1). 216–221. 146 indexed citations
16.
Samsom, Janneke N., Mascha Greuter, L A van Berkel, et al.. (2007). Blockade of IDO Inhibits Nasal Tolerance Induction. The Journal of Immunology. 179(2). 894–900. 32 indexed citations
17.
O’Toole, Tom & Maikel P. Peppelenbosch. (2006). Phosphatidyl inositol-3-phosphate kinase mediates CD14 dependent signaling. Molecular Immunology. 44(9). 2362–2369. 8 indexed citations
18.
Diks, Sander H., Klaartje Kok, Tom O’Toole, et al.. (2004). Kinome Profiling for Studying Lipopolysaccharide Signal Transduction in Human Peripheral Blood Mononuclear Cells. Journal of Biological Chemistry. 279(47). 49206–49213. 105 indexed citations
19.
Brink, Gijs R. van den, Tom O’Toole, James C.H. Hardwick, et al.. (2000). Leptin Signaling in Human Peripheral Blood Mononuclear Cells, Activation of p38 and p42/44 Mitogen-Activated Protein (MAP) Kinase and p70 S6 Kinase. PubMed. 4(3). 144–150. 52 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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