Tom Van Loy

2.1k total citations
65 papers, 1.6k citations indexed

About

Tom Van Loy is a scholar working on Oncology, Molecular Biology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Tom Van Loy has authored 65 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Oncology, 26 papers in Molecular Biology and 22 papers in Cellular and Molecular Neuroscience. Recurrent topics in Tom Van Loy's work include Chemokine receptors and signaling (26 papers), Neurobiology and Insect Physiology Research (17 papers) and Receptor Mechanisms and Signaling (12 papers). Tom Van Loy is often cited by papers focused on Chemokine receptors and signaling (26 papers), Neurobiology and Insect Physiology Research (17 papers) and Receptor Mechanisms and Signaling (12 papers). Tom Van Loy collaborates with scholars based in Belgium, United States and Netherlands. Tom Van Loy's co-authors include Jozef Vanden Broeck, Jeroen Poels, Matthias B. Van Hiel, Hans Peter Vandersmissen, Gert Simonet, Ilse Claeys, Gilbert Vassart, Arnold De Loof, Dominique Schols and Lieven Stuyver and has published in prestigious journals such as Journal of Biological Chemistry, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Tom Van Loy

61 papers receiving 1.6k 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 Van Loy Belgium 23 738 575 386 341 333 65 1.6k
Leif Søndergaard Denmark 15 570 0.8× 478 0.8× 327 0.8× 252 0.7× 131 0.4× 28 1.4k
Helmut Krämer United States 36 764 1.0× 2.9k 5.0× 779 2.0× 110 0.3× 106 0.3× 91 4.5k
Kumiko Ui‐Tei Japan 34 400 0.5× 3.9k 6.9× 696 1.8× 189 0.6× 216 0.6× 105 5.0k
Tessa G. Montague United States 12 188 0.3× 2.8k 5.0× 570 1.5× 194 0.6× 154 0.5× 16 3.5k
Michael R. Lerner United States 23 923 1.3× 2.8k 4.9× 621 1.6× 362 1.1× 211 0.6× 43 4.6k
István Andó Hungary 29 1.1k 1.5× 1.0k 1.7× 178 0.5× 1.8k 5.2× 173 0.5× 83 3.7k
Nicolas Nègre France 25 186 0.3× 2.1k 3.7× 339 0.9× 285 0.8× 65 0.2× 51 2.4k
M. Hirn France 33 1.3k 1.7× 1.4k 2.4× 593 1.5× 530 1.6× 427 1.3× 79 3.7k
Ward F. Odenwald United States 27 968 1.3× 2.3k 3.9× 592 1.5× 123 0.4× 127 0.4× 60 3.1k
Craig A. Mandato Canada 23 328 0.4× 1.2k 2.0× 99 0.3× 199 0.6× 85 0.3× 61 2.4k

Countries citing papers authored by Tom Van Loy

Since Specialization
Citations

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

Fields of papers citing papers by Tom Van Loy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tom Van Loy. 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 Van Loy. The network helps show where Tom Van Loy may publish in the future.

Co-authorship network of co-authors of Tom Van Loy

This figure shows the co-authorship network connecting the top 25 collaborators of Tom Van Loy. A scholar is included among the top collaborators of Tom Van Loy 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 Van Loy. Tom Van Loy 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
1.
Loy, Tom Van, Matti F. Pronker, Christopher Cawthorne, et al.. (2025). Indium-111-Labeled Single-Domain Antibody for In Vivo CXCR4 Imaging Using Single-Photon Emission Computed Tomography. Bioconjugate Chemistry. 36(4). 737–747.
2.
Tsutsumi, Naotaka, et al.. (2024). Insight into structural properties of viral G protein‐coupled receptors and their role in the viral infection: IUPHAR Review 41. British Journal of Pharmacology. 182(1). 26–51. 2 indexed citations
3.
Loy, Tom Van, Mike Sathekge, Christophe M. Deroose, et al.. (2024). Second generation Al18F-labeled D-amino acid peptide for CXCR4 targeted molecular imaging. Nuclear Medicine and Biology. 132-133. 108906–108906. 3 indexed citations
4.
5.
Renard, Isaline, Benjamin P. Burke, Abid Khan, et al.. (2024). Rigid Macrocycle Metal Complexes as CXCR4 Chemokine Receptor Antagonists: Influence of Ring Size. Pharmaceutics. 16(8). 1000–1000.
6.
Alzahrani, Seraj Omar, Graeme McRobbie, Abid Khan, et al.. (2024). trans-IV restriction: a new configuration for metal bis-cyclam complexes as potent CXCR4 inhibitors. Dalton Transactions. 53(12). 5616–5623. 3 indexed citations
7.
Kong, Qianqian, et al.. (2024). Development of a cellular model to study CCR8 signaling in tumor-infiltrating regulatory T cells. Cancer Immunology Immunotherapy. 73(1). 11–11. 3 indexed citations
8.
Loy, Tom Van, Sofie Celen, Michel Koole, et al.. (2024). Selective PET imaging of CXCR4 using the Al18F-labeled antagonist LY2510924. European Journal of Nuclear Medicine and Molecular Imaging. 52(5). 1723–1738. 2 indexed citations
9.
Schols, Dominique, et al.. (2023). REGA-SIGN: Development of a Novel Set of NanoBRET-Based G Protein Biosensors. Biosensors. 13(8). 767–767. 3 indexed citations
10.
Li, Qifei, Sandra Claes, Tom Van Loy, et al.. (2023). Synthesis and structure–activity relationship study of phenoxybenzylpiperazine analogues as CCR8 agonists. Bioorganic Chemistry. 139. 106755–106755.
11.
Loy, Tom Van, Steven De Jonghe, Karolien Castermans, et al.. (2022). Stimulation of the atypical chemokine receptor 3 (ACKR3) by a small-molecule agonist attenuates fibrosis in a preclinical liver but not lung injury model. Cellular and Molecular Life Sciences. 79(6). 293–293. 4 indexed citations
12.
Singh, Abhimanyu K., et al.. (2020). Development of a Novel SPR Assay to Study CXCR4–Ligand Interactions. Biosensors. 10(10). 150–150. 8 indexed citations
13.
Klarenbeek, A., Vladimir Bobkov, Jordi Doijen, et al.. (2018). CXCR4-targeting nanobodies differentially inhibit CXCR4 function and HIV entry. Biochemical Pharmacology. 158. 402–412. 43 indexed citations
14.
Claes, Sandra, et al.. (2018). CXCR7/ACKR3-targeting ligands interfere with X7 HIV-1 and HIV-2 entry and replication in human host cells. Heliyon. 4(3). e00557–e00557. 15 indexed citations
15.
Schols, Dominique, et al.. (2017). Comparison of cell-based assays for the identification and evaluation of competitive CXCR4 inhibitors. PLoS ONE. 12(4). e0176057–e0176057. 38 indexed citations
16.
Loy, Tom Van, et al.. (2010). The complexity of Drosophila innate immunity. SHILAP Revista de lepidopterología. 7(1). 32–44. 3 indexed citations
17.
Poels, Jeroen, Tom Van Loy, Hans Peter Vandersmissen, et al.. (2010). Myoinhibiting peptides are the ancestral ligands of the promiscuous Drosophila sex peptide receptor. Cellular and Molecular Life Sciences. 67(20). 3511–3522. 82 indexed citations
18.
Loy, Tom Van, et al.. (2007). How functional genomics and genetics complements insect endocrinology. General and Comparative Endocrinology. 155(1). 22–30. 12 indexed citations
19.
Loy, Tom Van, Matthias B. Van Hiel, Hans Peter Vandersmissen, et al.. (2006). Evolutionary conservation of bursicon in the animal kingdom. General and Comparative Endocrinology. 153(1-3). 59–63. 29 indexed citations
20.
Claeys, Ilse, Gert Simonet, Tom Van Loy, Arnold De Loof, & Jozef Vanden Broeck. (2003). cDNA cloning and transcript distribution of two novel members of the neuroparsin family in the desert locust, Schistocerca gregaria. Insect Molecular Biology. 12(5). 473–481. 41 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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