Roger S. Chung

7.5k total citations · 1 hit paper
141 papers, 5.5k citations indexed

About

Roger S. Chung is a scholar working on Molecular Biology, Neurology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Roger S. Chung has authored 141 papers receiving a total of 5.5k indexed citations (citations by other indexed papers that have themselves been cited), including 57 papers in Molecular Biology, 43 papers in Neurology and 32 papers in Cellular and Molecular Neuroscience. Recurrent topics in Roger S. Chung's work include Amyotrophic Lateral Sclerosis Research (31 papers), Trace Elements in Health (30 papers) and Alzheimer's disease research and treatments (22 papers). Roger S. Chung is often cited by papers focused on Amyotrophic Lateral Sclerosis Research (31 papers), Trace Elements in Health (30 papers) and Alzheimer's disease research and treatments (22 papers). Roger S. Chung collaborates with scholars based in Australia, China and United States. Roger S. Chung's co-authors include Adrian K. West, James C. Vickers, Bingyang Shi, Marco Morsch, Rowan A. W. Radford, Albert Lee, Meng Zheng, Dean L. Pountney, Gilles J. Guillemin and Meng Inn Chuah and has published in prestigious journals such as Nucleic Acids Research, Advanced Materials and Journal of Biological Chemistry.

In The Last Decade

Roger S. Chung

139 papers receiving 5.5k citations

Hit Papers

Microglia morphophysiological diversity and its implicati... 2022 2026 2023 2024 2022 50 100 150

Peers

Roger S. Chung
Wei‐Yi Ong Singapore
Torben Moos Denmark
Laura L. Dugan United States
Aaron B. Bowman United States
Feng Han China
Wei‐Yi Ong Singapore
Roger S. Chung
Citations per year, relative to Roger S. Chung Roger S. Chung (= 1×) peers Wei‐Yi Ong

Countries citing papers authored by Roger S. Chung

Since Specialization
Citations

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

Fields of papers citing papers by Roger S. Chung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Roger S. Chung. 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 Roger S. Chung. The network helps show where Roger S. Chung may publish in the future.

Co-authorship network of co-authors of Roger S. Chung

This figure shows the co-authorship network connecting the top 25 collaborators of Roger S. Chung. A scholar is included among the top collaborators of Roger S. Chung 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 Roger S. Chung. Roger S. Chung 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.
Davidson, Jennilee M., Lívia Rosa-Fernandes, Rebecca San Gil, et al.. (2025). Proteomics Analysis of the TDP ‐43 Interactome in Cellular Models of ALS Pathogenesis. Journal of Neurochemistry. 169(5). e70079–e70079. 1 indexed citations
2.
Farrawell, Natalie E., Luke McAlary, Dzung Do‐Ha, et al.. (2023). ALS-linked CCNF variant disrupts motor neuron ubiquitin homeostasis. Human Molecular Genetics. 32(14). 2386–2398. 4 indexed citations
3.
Fu, Libing, Bingyang Shi, Shihui Wen, et al.. (2022). Aspect Ratio of PEGylated Upconversion Nanocrystals Affects the Cellular Uptake In Vitro and In Vivo. Acta Biomaterialia. 147. 403–413. 19 indexed citations
4.
Watchon, Maxinne, Luan Luu, Katherine J. Robinson, et al.. (2021). Sodium valproate increases activity of the sirtuin pathway resulting in beneficial effects for spinocerebellar ataxia-3 in vivo. Molecular Brain. 14(1). 14 indexed citations
5.
Wright, Amanda L., Paul A. Della Gatta, Sheng Le, et al.. (2021). Riluzole does not ameliorate disease caused by cytoplasmic TDP‐43 in a mouse model of amyotrophic lateral sclerosis. European Journal of Neuroscience. 54(6). 6237–6255. 16 indexed citations
6.
Don, Emily K., Rowan A. W. Radford, Natalie M. Scherer, et al.. (2021). In vivo Validation of Bimolecular Fluorescence Complementation (BiFC) to Investigate Aggregate Formation in Amyotrophic Lateral Sclerosis (ALS). Molecular Neurobiology. 58(5). 2061–2074. 9 indexed citations
7.
Muhammad, Pir, Sumaira Hanif, Fawad Ur Rehman, et al.. (2021). Correction: SERS-based nanostrategy for rapid anemia diagnosis. Nanoscale. 13(37). 15981–15981. 2 indexed citations
8.
Wang, Guoying, et al.. (2020). Advances in nanotechnology-based strategies for the treatments of amyotrophic lateral sclerosis. Materials Today Bio. 6. 100055–100055. 49 indexed citations
9.
Liu, Yanjie, Yan Zou, Chan Feng, et al.. (2020). Charge Conversional Biomimetic Nanocomplexes as a Multifunctional Platform for Boosting Orthotopic Glioblastoma RNAi Therapy. Nano Letters. 20(3). 1637–1646. 145 indexed citations
10.
Lewis, Katherine E., William M. Bennett, Christopher Leigh Blizzard, et al.. (2020). The influence of metallothionein treatment and treadmill running exercise on disease onset and survival in SOD1 G93A amyotrophic lateral sclerosis mice. European Journal of Neuroscience. 52(4). 3223–3241. 2 indexed citations
11.
Mahan, Brandon, Roger S. Chung, Dean L. Pountney, Frédéric Moynier, & Simon Turner. (2020). Isotope metallomics approaches for medical research. Cellular and Molecular Life Sciences. 77(17). 3293–3309. 26 indexed citations
12.
Rayner, Stephanie L., Marco Morsch, Mark P. Molloy, et al.. (2019). Using proteomics to identify ubiquitin ligase–substrate pairs: how novel methods may unveil therapeutic targets for neurodegenerative diseases. Cellular and Molecular Life Sciences. 76(13). 2499–2510. 17 indexed citations
13.
Muhammad, Pir, Sumaira Hanif, Fawad Ur Rehman, et al.. (2019). SERS-based nanostrategy for rapid anemia diagnosis. Nanoscale. 12(3). 1948–1957. 17 indexed citations
14.
Ruan, Weimin, Meng Zheng, Yuanyuan Liu, et al.. (2018). DNA nanoclew templated spherical nucleic acids for siRNA delivery. Chemical Communications. 54(29). 3609–3612. 52 indexed citations
15.
Shi, Bingyang, Meng Zheng, Wei Tao, et al.. (2017). Challenges in DNA Delivery and Recent Advances in Multifunctional Polymeric DNA Delivery Systems. Biomacromolecules. 18(8). 2231–2246. 166 indexed citations
16.
Fu, Libing, Marco Morsch, Bingyang Shi, et al.. (2017). A versatile upconversion surface evaluation platform for bio–nano surface selection for the nervous system. Nanoscale. 9(36). 13683–13692. 15 indexed citations
17.
Don, Emily K., Andrew P. Badrock, Thomas E. Hall, et al.. (2016). A Tol2 Gateway-Compatible Toolbox for the Study of the Nervous System and Neurodegenerative Disease. Zebrafish. 14(1). 69–72. 45 indexed citations
18.
Radford, Rowan A. W., et al.. (2016). SOD1 Pathology in ALS: TDP or not TDP that is the Question. 2(3). 1–4. 1 indexed citations
19.
Gupta, Vivek, Nitin Chitranshi, Veer Bala Gupta, et al.. (2016). Amyloid β accumulation and inner retinal degenerative changes in Alzheimer’s disease transgenic mouse. Neuroscience Letters. 623. 52–56. 95 indexed citations
20.
Lewis, Katherine E., William Bennett, Anna E. King, et al.. (2014). Microglia and motor neurons during disease progression in the SOD1G93A mouse model of amyotrophic lateral sclerosis: changes in arginase1 and inducible nitric oxide synthase. Journal of Neuroinflammation. 11(1). 55–55. 55 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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