Yan Shen

6.4k total citations
109 papers, 4.2k citations indexed

About

Yan Shen is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Genetics. According to data from OpenAlex, Yan Shen has authored 109 papers receiving a total of 4.2k indexed citations (citations by other indexed papers that have themselves been cited), including 69 papers in Molecular Biology, 35 papers in Cellular and Molecular Neuroscience and 24 papers in Genetics. Recurrent topics in Yan Shen's work include Neuroscience and Neuropharmacology Research (15 papers), Genetics and Neurodevelopmental Disorders (15 papers) and RNA modifications and cancer (10 papers). Yan Shen is often cited by papers focused on Neuroscience and Neuropharmacology Research (15 papers), Genetics and Neurodevelopmental Disorders (15 papers) and RNA modifications and cancer (10 papers). Yan Shen collaborates with scholars based in China, United States and United Kingdom. Yan Shen's co-authors include Qi Xu, Wenbin Deng, Jennifer M. Plane, David Pleasure, Wilson H.Y. Lo, Yun Tan, Lian Yuan Cao, Dong Zhou, Kerang Zhang and Jianbo Xiu and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Nucleic Acids Research.

In The Last Decade

Yan Shen

108 papers receiving 4.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yan Shen China 35 2.1k 863 706 514 420 109 4.2k
Hideo Matsuzaki Japan 34 2.4k 1.1× 1.0k 1.2× 1.1k 1.5× 472 0.9× 320 0.8× 125 5.3k
Angela M. Kaindl Germany 34 2.0k 0.9× 960 1.1× 568 0.8× 480 0.9× 218 0.5× 166 4.6k
Guoyin Feng China 40 2.6k 1.2× 933 1.1× 1.3k 1.9× 732 1.4× 427 1.0× 172 5.0k
Qi Xu China 32 1.3k 0.6× 637 0.7× 438 0.6× 410 0.8× 501 1.2× 133 2.9k
Serge Weis Germany 37 1.3k 0.6× 846 1.0× 260 0.4× 553 1.1× 558 1.3× 150 4.9k
Chul Hoon Kim South Korea 34 2.2k 1.0× 1.2k 1.3× 538 0.8× 163 0.3× 187 0.4× 138 4.8k
Diane C. Lagace Canada 36 1.9k 0.9× 1.2k 1.4× 447 0.6× 202 0.4× 249 0.6× 70 4.4k
Ji‐Eun Kim South Korea 41 3.2k 1.5× 2.5k 2.9× 752 1.1× 420 0.8× 216 0.5× 181 6.8k
Ken Inoue Japan 35 2.5k 1.2× 760 0.9× 1.3k 1.8× 253 0.5× 104 0.2× 175 4.6k
Mark L. Day United States 45 3.0k 1.4× 1.3k 1.5× 776 1.1× 266 0.5× 119 0.3× 117 6.6k

Countries citing papers authored by Yan Shen

Since Specialization
Citations

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

Fields of papers citing papers by Yan Shen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yan Shen

This figure shows the co-authorship network connecting the top 25 collaborators of Yan Shen. A scholar is included among the top collaborators of Yan Shen 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 Yan Shen. Yan Shen 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.
Xiu, Jianbo, Jiayu Li, Zeyue Liu, et al.. (2022). Elevated BICD2 DNA methylation in blood of major depressive disorder patients and reduction of depressive-like behaviors in hippocampal Bicd2 -knockdown mice. Proceedings of the National Academy of Sciences. 119(30). e2201967119–e2201967119. 25 indexed citations
2.
Wei, Hui, et al.. (2017). Decreased Prostaglandin D2 Levels in Major Depressive Disorder Are Associated with Depression-Like Behaviors. The International Journal of Neuropsychopharmacology. 20(9). 731–739. 30 indexed citations
3.
Ye, Ning, Shuquan Rao, Tingfu Du, et al.. (2016). Intergenic variants may predispose to major depression disorder through regulation of long non-coding RNA expression. Gene. 601. 21–26. 31 indexed citations
4.
Du, Tingfu, et al.. (2016). Inverse changes in L1 retrotransposons between blood and brain in major depressive disorder. Scientific Reports. 6(1). 37530–37530. 30 indexed citations
5.
Du, Tingfu, Shuquan Rao, Lin Wu, et al.. (2015). An association study of the m6A genes with major depressive disorder in Chinese Han population. Journal of Affective Disorders. 183. 279–286. 90 indexed citations
6.
Sun, Yuhui, Haihong Ye, Li Zhu, et al.. (2015). Increased dysbindin-1B isoform expression in schizophrenia and its propensity in aggresome formation. Cell Discovery. 1(1). 15032–15032. 13 indexed citations
7.
Lin, Dong, Ning Zhu, Le Wang, et al.. (2012). Isolation of siRNA target by biotinylated siRNA reveals that human CCDC12 promotes early erythroid differentiation. Leukemia Research. 36(6). 779–783. 8 indexed citations
8.
Shi, Cuijuan, et al.. (2012). A study of the combined effects of the EHD3 and FREM3 genes in patients with major depressive disorder. American Journal of Medical Genetics Part B Neuropsychiatric Genetics. 159B(3). 336–342. 8 indexed citations
9.
Chen, Jun, Yong Xu, Juan Zhang, et al.. (2012). Genotypic Association of the DAOA Gene with Resting-State Brain Activity in Major Depression. Molecular Neurobiology. 46(2). 361–373. 19 indexed citations
10.
Rao, Shaoqi, et al.. (2011). Newborn hearing concurrent gene screening can improve care for hearing loss: A study on 14,913 Chinese newborns. International Journal of Pediatric Otorhinolaryngology. 75(4). 535–542. 56 indexed citations
11.
Sun, Yuhui, et al.. (2011). Study of a possible role of the monoamine oxidase A (MAOA) gene in paranoid schizophrenia among a Chinese population. American Journal of Medical Genetics Part B Neuropsychiatric Genetics. 159B(1). 104–111. 19 indexed citations
12.
Wang, Baoxi, Wei Yang, Wen Wen, et al.. (2010). γ-Secretase Gene Mutations in Familial Acne Inversa. Science. 330(6007). 1065–1065. 298 indexed citations
13.
Wang, Zhao‐Qi, et al.. (2006). PARP1 Val762Ala polymorphism reduces enzymatic activity. Biochemical and Biophysical Research Communications. 354(1). 122–126. 105 indexed citations
14.
Ren, Liankun, Liri Jin, Boyu Zhang, et al.. (2005). Lack of GABABR1 gene variation (G1465A) in a Chinese population with temporal lobe epilepsy. Seizure. 14(8). 611–613. 9 indexed citations
16.
Zhang, Boyu, Yanbo Yuan, Yanbin Jia, et al.. (2004). An association study between polymorphisms in five genes in glutamate and GABA pathway and paranoid schizophrenia. European Psychiatry. 20(1). 45–49. 21 indexed citations
17.
Xu, Qi, Ying‐Ping Wang, Yan Shen, et al.. (2004). Association study of an SNP combination pattern in the dopaminergic pathway in paranoid schizophrenia: a novel strategy for complex disorders. Molecular Psychiatry. 9(5). 510–521. 33 indexed citations
18.
Yan, Weili, Shufeng Chen, Jianfeng Huang, et al.. (2004). Polymorphisms in PLIN and Hypertension Combined with Obesity and Lipid Profiles in Han Chinese. Obesity Research. 12(11). 1733–1737. 21 indexed citations
19.
Chen, Yucai, Jianjun Lu, Hong Pan, et al.. (2003). Association between genetic variation of CACNA1H and childhood absence epilepsy. Annals of Neurology. 54(2). 239–243. 277 indexed citations
20.
Lu, Jianjun, Yucai Chen, Yuehua Zhang, et al.. (2002). Mutation screen of the GABAA receptor gamma 2 subunit gene in Chinese patients with childhood absence epilepsy. Neuroscience Letters. 332(2). 75–78. 13 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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