Garry Wong

6.6k total citations · 2 hit papers
139 papers, 5.1k citations indexed

About

Garry Wong is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Aging. According to data from OpenAlex, Garry Wong has authored 139 papers receiving a total of 5.1k indexed citations (citations by other indexed papers that have themselves been cited), including 88 papers in Molecular Biology, 55 papers in Cellular and Molecular Neuroscience and 28 papers in Aging. Recurrent topics in Garry Wong's work include Neuroscience and Neuropharmacology Research (38 papers), Genetics, Aging, and Longevity in Model Organisms (28 papers) and Gene expression and cancer classification (15 papers). Garry Wong is often cited by papers focused on Neuroscience and Neuropharmacology Research (38 papers), Genetics, Aging, and Longevity in Model Organisms (28 papers) and Gene expression and cancer classification (15 papers). Garry Wong collaborates with scholars based in Finland, United States and Macao. Garry Wong's co-authors include Eero Ċastrén, Merja Lakso, Liang Chen, Changliang Wang, Petri Törönen, Huiyan Sun, Liisa Heikkinen, Richard Nass, Mikko Kolehmainen and Phil Skolnick and has published in prestigious journals such as Nucleic Acids Research, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Garry Wong

137 papers receiving 4.9k citations

Hit Papers

Trends in the development of miRNA bioinformatics tools 2018 2026 2020 2023 2018 2020 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Garry Wong Finland 38 2.8k 1.5k 875 519 445 139 5.1k
Ari Barzilai Israel 38 3.1k 1.1× 2.0k 1.3× 584 0.7× 75 0.1× 517 1.2× 93 5.2k
Zengqiang Yuan China 51 5.5k 2.0× 730 0.5× 1.0k 1.2× 408 0.8× 330 0.7× 140 8.6k
Zhong‐Ping Feng Canada 46 3.4k 1.3× 1.7k 1.1× 656 0.7× 91 0.2× 297 0.7× 184 6.8k
Mark P. Mattson United States 35 2.1k 0.8× 1.5k 1.0× 338 0.4× 225 0.4× 278 0.6× 39 4.9k
Susan L. Ackerman United States 43 5.0k 1.8× 2.2k 1.5× 333 0.4× 122 0.2× 308 0.7× 79 7.2k
Calum Sutherland United Kingdom 45 5.1k 1.9× 1.2k 0.9× 373 0.4× 117 0.2× 205 0.5× 111 8.1k
Paul L. Greer United States 16 2.8k 1.0× 1.3k 0.9× 295 0.3× 484 0.9× 64 0.1× 26 5.2k
Bryce L. Sopher United States 38 3.7k 1.3× 2.3k 1.6× 343 0.4× 119 0.2× 618 1.4× 63 6.0k
Wenjun Li China 43 1.9k 0.7× 632 0.4× 314 0.4× 127 0.2× 242 0.5× 186 5.0k
Sic L. Chan United States 44 3.6k 1.3× 2.1k 1.4× 399 0.5× 162 0.3× 534 1.2× 83 8.1k

Countries citing papers authored by Garry Wong

Since Specialization
Citations

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

Fields of papers citing papers by Garry Wong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Garry Wong

This figure shows the co-authorship network connecting the top 25 collaborators of Garry Wong. A scholar is included among the top collaborators of Garry Wong 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 Garry Wong. Garry Wong 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.
Bordin, Diana L., Veslemøy Rolseth, Lisa Lirussi, et al.. (2025). SMUG1 DNA glycosylase modulates reward behaviour through regulation of olfactory receptor gene expression. Nucleic Acids Research. 53(14). 1 indexed citations
2.
Chen, Yuqi, Changliang Wang, Maoni Guo, et al.. (2025). MOGAD: Integrated Multi-Omics and Graph Attention for the Discovery of Alzheimer’s Disease’s Biomarkers. Informatics. 12(3). 68–68.
3.
Zhang, Tianjiao, Liang Chen, Haibin Zhu, & Garry Wong. (2025). Mammalian piRNA target prediction using a hierarchical attention model. BMC Bioinformatics. 26(1). 50–50.
4.
Chen, Yuqi, Xiaomin Liang, Wei Du, et al.. (2024). Drug–Target Interaction Prediction Based on an Interactive Inference Network. International Journal of Molecular Sciences. 25(14). 7753–7753. 2 indexed citations
5.
Li, Rongzhen, et al.. (2024). Novel C. elegans models of Lewy body disease reveal pathological protein interactions and widespread miRNA dysregulation. Cellular and Molecular Life Sciences. 81(1). 377–377. 2 indexed citations
6.
Huang, Xiaobing, Changliang Wang, Tianjiao Zhang, et al.. (2023). PIWI-interacting RNA expression regulates pathogenesis in a Caenorhabditis elegans model of Lewy body disease. Nature Communications. 14(1). 6137–6137. 13 indexed citations
7.
Zhang, Tianjiao, et al.. (2022). PIWI-interacting RNAs in human diseases: databases and computational models. Briefings in Bioinformatics. 23(4). 11 indexed citations
9.
Chen, Liang, Changliang Wang, Huiyan Sun, et al.. (2020). The bioinformatics toolbox for circRNA discovery and analysis. Briefings in Bioinformatics. 22(2). 1706–1728. 266 indexed citations breakdown →
10.
Chen, Liang, Huiyan Sun, Changliang Wang, et al.. (2018). miRNA arm switching identifies novel tumour biomarkers. EBioMedicine. 38. 37–46. 29 indexed citations
11.
Wong, Garry, et al.. (2015). Perspectives on Caenorhabditis elegans models of human Parkinson’s Disease. ADMET & DMPK. 3(2). 122–130. 1 indexed citations
12.
Pihlaja, Rea, Eveliina Pollari, Katja M. Kanninen, et al.. (2012). Adult and neonatal astrocytes exhibit diverse gene expression profiles in response to beta amyloid <i>ex vivo</i>. World Journal of Neuroscience. 2(2). 57–67. 6 indexed citations
13.
Baverstock, Keith, Mikko Hiltunen, Merja Korkalainen, et al.. (2012). Radiation-induced genomic instability in Caenorhabditis elegans. Mutation Research/Genetic Toxicology and Environmental Mutagenesis. 748(1-2). 36–41. 11 indexed citations
14.
VanDuyn, Natalia, Raja S. Settivari, Garry Wong, & Richard Nass. (2010). SKN-1/Nrf2 Inhibits Dopamine Neuron Degeneration in a Caenorhabditis elegans Model of Methylmercury Toxicity. Toxicological Sciences. 118(2). 613–624. 84 indexed citations
15.
Sinkkonen, Saku T., A. Linden, Esa R. Korpi, & Garry Wong. (2004). Selective reduction of γ-aminobutyric acid type A receptor δ subunit mRNA levels by MK-801 in rat dentate gyrus. Neuroscience Letters. 364(2). 106–109. 5 indexed citations
16.
Linden, A., Markus Storvik, Merja Lakso, et al.. (2001). Increased expression of neuronal Src and tyrosine phosphorylation of NMDA receptors in rat brain after systemic treatment with MK-801. Neuropharmacology. 40(4). 469–481. 8 indexed citations
17.
Haapasalo, Annakaisa, Eija Koponen, Edmund Hoppe, Garry Wong, & Eero Ċastrén. (2001). Truncated trkB.T1 Is Dominant Negative Inhibitor of trkB.TK+-Mediated Cell Survival. Biochemical and Biophysical Research Communications. 280(5). 1352–1358. 116 indexed citations
18.
Acri, Jane B., et al.. (1997). Localization and pharmacological characterization of pigeon diazepam-insensitive GABAA receptors. Neuroscience. 77(2). 371–378. 5 indexed citations
19.
Wong, Garry, Konrad F. Koehler, Phil Skolnick, et al.. (1993). Synthetic and computer-assisted analysis of the structural requirements for selective, high-affinity ligand binding to diazepam-insensitive benzodiazepine receptors. Journal of Medicinal Chemistry. 36(13). 1820–1830. 49 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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