Riqiang Yan

11.8k total citations · 3 hit papers
99 papers, 8.1k citations indexed

About

Riqiang Yan is a scholar working on Physiology, Molecular Biology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Riqiang Yan has authored 99 papers receiving a total of 8.1k indexed citations (citations by other indexed papers that have themselves been cited), including 69 papers in Physiology, 45 papers in Molecular Biology and 20 papers in Cellular and Molecular Neuroscience. Recurrent topics in Riqiang Yan's work include Alzheimer's disease research and treatments (68 papers), Cholinesterase and Neurodegenerative Diseases (16 papers) and Neuroinflammation and Neurodegeneration Mechanisms (13 papers). Riqiang Yan is often cited by papers focused on Alzheimer's disease research and treatments (68 papers), Cholinesterase and Neurodegenerative Diseases (16 papers) and Neuroinflammation and Neurodegeneration Mechanisms (13 papers). Riqiang Yan collaborates with scholars based in United States, China and Russia. Riqiang Yan's co-authors include Robert Vassar, Xiangyou Hu, Wanxia He, Philip C. Wong, Brati Das, Michael J. Bienkowski, Dora M. Kovacs, Mary E. Shuck, Huiyi Miao and Bruce D. Trapp and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Riqiang Yan

97 papers receiving 8.0k citations

Hit Papers

Membrane-anchored aspartyl protease with Alzheimer's dise... 1999 2026 2008 2017 1999 2014 2017 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Riqiang Yan United States 42 4.4k 3.3k 1.8k 1.4k 1.3k 99 8.1k
Stefan F. Lichtenthaler Germany 55 4.3k 1.0× 4.2k 1.3× 1.4k 0.8× 1.3k 1.0× 910 0.7× 182 9.0k
Nobuhisa Iwata Japan 50 6.8k 1.5× 4.4k 1.3× 1.8k 1.0× 2.9k 2.1× 861 0.7× 142 11.6k
Steven Estus United States 44 4.4k 1.0× 4.4k 1.4× 933 0.5× 1.5k 1.1× 526 0.4× 87 8.3k
Jochen Walter Germany 60 6.0k 1.3× 5.3k 1.6× 1.5k 0.8× 2.3k 1.7× 740 0.6× 148 11.6k
Mary Jo LaDu United States 51 7.1k 1.6× 3.8k 1.2× 1.3k 0.7× 2.0k 1.5× 962 0.8× 105 9.6k
Tilman Oltersdorf United States 33 5.0k 1.1× 5.9k 1.8× 1.3k 0.7× 1.2k 0.9× 874 0.7× 52 10.4k
M. Paul Murphy United States 43 5.8k 1.3× 3.4k 1.0× 1.4k 0.8× 2.1k 1.5× 732 0.6× 75 8.9k
Luciano D'adamio United States 47 3.5k 0.8× 3.9k 1.2× 953 0.5× 1.5k 1.1× 362 0.3× 109 7.1k
Jorge Busciglio United States 43 4.3k 1.0× 3.5k 1.1× 996 0.6× 1.7k 1.2× 392 0.3× 65 7.9k
Gopal Thinakaran United States 57 8.9k 2.0× 6.0k 1.8× 2.2k 1.2× 2.5k 1.8× 958 0.8× 121 12.1k

Countries citing papers authored by Riqiang Yan

Since Specialization
Citations

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

Fields of papers citing papers by Riqiang Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Riqiang Yan

This figure shows the co-authorship network connecting the top 25 collaborators of Riqiang Yan. A scholar is included among the top collaborators of Riqiang Yan 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 Riqiang Yan. Riqiang Yan 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.
Leclair, Nathan K., Omar M. Omar, Aamir Zuberi, et al.. (2025). Amyotrophic lateral sclerosis and frontotemporal dementia mutation reduces endothelial TDP-43 and causes blood-brain barrier defects. Science Advances. 11(16). eads0505–eads0505. 3 indexed citations
2.
Huang, Hao, Md Golam Sharoar, Liang‐Liang Fan, et al.. (2024). Accumulation of neutral lipids in dystrophic neurites surrounding amyloid plaques in Alzheimer's disease. Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease. 1870(4). 167086–167086. 4 indexed citations
3.
Li, Xu‐Hui, et al.. (2024). Increased gene dosage of RFWD2 causes autistic-like behaviors and aberrant synaptic formation and function in mice. Molecular Psychiatry. 29(8). 2496–2509. 5 indexed citations
5.
Ishii, Akihiro, Omar M. Omar, Yingying Ge, et al.. (2024). Contribution of amyloid deposition from oligodendrocytes in a mouse model of Alzheimer’s disease. Molecular Neurodegeneration. 19(1). 83–83. 10 indexed citations
7.
Iqbal, Javed, et al.. (2023). Klotho Regulated by Estrogen Plays a Key Role in Sex Differences in Stress Resilience in Rats. International Journal of Molecular Sciences. 24(2). 1206–1206. 20 indexed citations
8.
Zhou, John, Qi Shi, Wanxia He, et al.. (2023). Reticulons 1 and 3 are essential for axonal growth and synaptic maintenance associated with intellectual development. Human Molecular Genetics. 32(16). 2587–2599. 2 indexed citations
9.
Sharoar, Md Golam, Xiangyou Hu, Xin‐Ming Ma, Xiongwei Zhu, & Riqiang Yan. (2019). Sequential formation of different layers of dystrophic neurites in Alzheimer’s brains. Molecular Psychiatry. 24(9). 1369–1382. 54 indexed citations
10.
Das, Brati & Riqiang Yan. (2017). Role of BACE1 in Alzheimer’s synaptic function. Translational Neurodegeneration. 6(1). 23–23. 99 indexed citations
11.
Yan, Riqiang. (2016). Stepping closer to treating Alzheimer’s disease patients with BACE1 inhibitor drugs. Translational Neurodegeneration. 5(1). 13–13. 81 indexed citations
12.
Hu, Xiangyou, Qingyuan Fan, Hailong Hou, & Riqiang Yan. (2015). Neurological dysfunctions associated with altered BACE1‐dependent Neuregulin‐1 signaling. Journal of Neurochemistry. 136(2). 234–249. 41 indexed citations
13.
Luo, Xiaoyang, Wanxia He, Xiangyou Hu, & Riqiang Yan. (2013). Reversible Overexpression of Bace1-Cleaved Neuregulin-1 N-Terminal Fragment Induces Schizophrenia-Like Phenotypes in Mice. Biological Psychiatry. 76(2). 120–127. 43 indexed citations
14.
Prior, Marguerite, et al.. (2010). RTN/Nogo in forming Alzheimer's neuritic plaques. Neuroscience & Biobehavioral Reviews. 34(8). 1201–1206. 20 indexed citations
15.
Heath, Jonathon, Sandra L. Siedlak, Xiongwei Zhu, et al.. (2010). Widespread distribution of reticulon-3 in various neurodegenerative diseases. Neuropathology. 30(6). 574–579. 18 indexed citations
16.
Yan, Riqiang. (2009). CHI's Eighth Annual World Pharmaceutical Congress. Targeting Alzheimer's with novel therapeutics: Part 2.. PubMed. 12(8). 482–4. 1 indexed citations
17.
Shi, Qi, Marguerite Prior, Wanxia He, et al.. (2009). Reduced Amyloid Deposition in Mice Overexpressing RTN3 Is Adversely Affected by Preformed Dystrophic Neurites. Journal of Neuroscience. 29(29). 9163–9173. 52 indexed citations
18.
Breij, Esther C.W., Rob Veerhuis, Rianka P. M. Vloet, et al.. (2008). Homogeneity of active demyelinating lesions in established multiple sclerosis. Annals of Neurology. 63(1). 16–25. 255 indexed citations
19.
He, Wanxia, Qi Shi, Xiangyou Hu, & Riqiang Yan. (2007). The Membrane Topology of RTN3 and Its Effect on Binding of RTN3 to BACE1. Journal of Biological Chemistry. 282(40). 29144–29151. 38 indexed citations
20.
Li, Jinhe, Adele M. Pauley, John R. Brashler, et al.. (2002). SEL‐10 interacts with presenilin 1, facilitates its ubiquitination, and alters A‐beta peptide production. Journal of Neurochemistry. 82(6). 1540–1548. 58 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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