Qijiang Yan

1.2k total citations
9 papers, 940 citations indexed

About

Qijiang Yan is a scholar working on Molecular Biology, Cognitive Neuroscience and Genetics. According to data from OpenAlex, Qijiang Yan has authored 9 papers receiving a total of 940 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 4 papers in Cognitive Neuroscience and 4 papers in Genetics. Recurrent topics in Qijiang Yan's work include Genetics and Neurodevelopmental Disorders (4 papers), Autism Spectrum Disorder Research (4 papers) and Platelet Disorders and Treatments (2 papers). Qijiang Yan is often cited by papers focused on Genetics and Neurodevelopmental Disorders (4 papers), Autism Spectrum Disorder Research (4 papers) and Platelet Disorders and Treatments (2 papers). Qijiang Yan collaborates with scholars based in China, United States and Canada. Qijiang Yan's co-authors include Robert Bauchwitz, Michael R. Tranfaglia, Mustapha Rammal, Richard E. Brown, Riccardo Bianchi, Wangfa Zhao, Robert K. S. Wong, Shih‐Chieh Chuang, Christopher J. Yuskaitis and Shengqiang Chen and has published in prestigious journals such as Journal of Neuroscience, SHILAP Revista de lepidopterología and Neuropharmacology.

In The Last Decade

Qijiang Yan

9 papers receiving 928 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Qijiang Yan China	7	729	585	498	221	84	9	940
Vijayendran Chandran United States	11	542 0.7×	709 1.2×	379 0.8×	169 0.8×	75 0.9×	16	1.1k
Brian P. Larsen United States	4	642 0.9×	504 0.9×	396 0.8×	181 0.8×	114 1.4×	5	841
Robert Bauchwitz United States	10	771 1.1×	683 1.2×	495 1.0×	190 0.9×	50 0.6×	11	1.0k
Alice Zhang United States	4	437 0.6×	502 0.9×	335 0.7×	231 1.0×	141 1.7×	6	942
Matthew C. Judson United States	16	754 1.0×	593 1.0×	207 0.4×	140 0.6×	80 1.0×	20	947
Gregory J. Pelka Australia	14	783 1.1×	597 1.0×	347 0.7×	101 0.5×	60 0.7×	14	1.0k
John B. Vincent Canada	11	878 1.2×	656 1.1×	539 1.1×	113 0.5×	36 0.4×	19	1.1k
Giuseppina Lonetti Italy	6	424 0.6×	390 0.7×	241 0.5×	184 0.8×	93 1.1×	8	693
Ronald A.M. Buijsen Netherlands	15	543 0.7×	599 1.0×	294 0.6×	291 1.3×	42 0.5×	31	827
Amber Hogart United States	10	1.2k 1.6×	972 1.7×	627 1.3×	115 0.5×	42 0.5×	10	1.5k

Countries citing papers authored by Qijiang Yan

Since Specialization

Citations

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

Fields of papers citing papers by Qijiang Yan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qijiang Yan

This figure shows the co-authorship network connecting the top 25 collaborators of Qijiang Yan. A scholar is included among the top collaborators of Qijiang 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 Qijiang Yan. Qijiang Yan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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9 of 9 papers shown

Zhu, Xiaoyan, et al.. (2022). Dietary Supplementation With Acer truncatum Oil Promotes Remyelination in a Mouse Model of Multiple Sclerosis. Frontiers in Neuroscience. 16. 860280–860280. 7 indexed citations

Ren, Guoping, et al.. (2019). Research Progress on Detection Methods of Amphetamines in Human Hair.. SHILAP Revista de lepidopterología. 35(1). 89–94. 1 indexed citations

Sun, Liwei, Qijiang Yan, Yonghua Wang, et al.. (2018). Pathogenicity analysis of variations and prenatal diagnosis in a hereditary coagulation factor XIII deficiency family. Hematology. 23(8). 501–509. 6 indexed citations

Wang, Jianru, et al.. (2017). Establishing a comprehensive genetic diagnosis strategy for hemophilia B and its application in Chinese population. International Journal of Laboratory Hematology. 40(2). 215–228. 1 indexed citations

Liu, Feifei, Aiguo Xuan, Yan Chen, et al.. (2014). Combined effect of nerve growth factor and brain-derived neurotrophic factor on neuronal differentiation of neural stem cells and the potential molecular mechanisms. Molecular Medicine Reports. 10(4). 1739–1745. 73 indexed citations

Yuskaitis, Christopher J., et al.. (2008). Elevated glycogen synthase kinase-3 activity in Fragile X mice: Key metabolic regulator with evidence for treatment potential. Neuropharmacology. 56(2). 463–472. 114 indexed citations

Yan, Qijiang, Mustapha Rammal, Michael R. Tranfaglia, & Robert Bauchwitz. (2005). Suppression of two major Fragile X Syndrome mouse model phenotypes by the mGluR5 antagonist MPEP. Neuropharmacology. 49(7). 1053–1066. 421 indexed citations

Chuang, Shih‐Chieh, Wangfa Zhao, Robert Bauchwitz, et al.. (2005). Prolonged Epileptiform Discharges Induced by Altered Group I Metabotropic Glutamate Receptor-Mediated Synaptic Responses in Hippocampal Slices of a Fragile X Mouse Model. Journal of Neuroscience. 25(35). 8048–8055. 157 indexed citations

Yan, Qijiang, et al.. (2004). A phenotypic and molecular characterization of the fmr1‐tm1Cgr Fragile X mouse. Genes Brain & Behavior. 3(6). 337–359. 160 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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