Yiru Fang

10.3k total citations · 1 hit paper
257 papers, 5.6k citations indexed

About

Yiru Fang is a scholar working on Psychiatry and Mental health, Pharmacology and Biological Psychiatry. According to data from OpenAlex, Yiru Fang has authored 257 papers receiving a total of 5.6k indexed citations (citations by other indexed papers that have themselves been cited), including 101 papers in Psychiatry and Mental health, 74 papers in Pharmacology and 62 papers in Biological Psychiatry. Recurrent topics in Yiru Fang's work include Bipolar Disorder and Treatment (78 papers), Treatment of Major Depression (71 papers) and Tryptophan and brain disorders (62 papers). Yiru Fang is often cited by papers focused on Bipolar Disorder and Treatment (78 papers), Treatment of Major Depression (71 papers) and Tryptophan and brain disorders (62 papers). Yiru Fang collaborates with scholars based in China, United States and Canada. Yiru Fang's co-authors include Zhiguo Wu, Jun Chen, Zezhi Li, Daihui Peng, Wu Hong, Chen Zhang, Chengmei Yuan, Shunying Yu, Zuowei Wang and Zhenghui Yi and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Yiru Fang

247 papers receiving 5.5k citations

Hit Papers

Major Depressive Disorder... 2021 2026 2022 2024 2021 50 100 150

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yiru Fang China 42 1.6k 1.3k 1.1k 1.1k 965 257 5.6k
Joanna Hauser Poland 36 1.6k 1.0× 1.1k 0.8× 789 0.7× 753 0.7× 658 0.7× 158 4.5k
Tiago Reis Marques United Kingdom 37 2.2k 1.4× 1.2k 0.9× 1.3k 1.1× 939 0.9× 828 0.9× 112 5.5k
Taro Kishi Japan 42 1.9k 1.2× 834 0.6× 781 0.7× 883 0.8× 990 1.0× 233 5.5k
Katherine J. Aitchison United Kingdom 44 1.9k 1.2× 1.7k 1.3× 716 0.6× 664 0.6× 1.1k 1.2× 159 6.0k
Breno S. Diniz Brazil 52 3.1k 2.0× 1.3k 1.0× 1.2k 1.0× 1.5k 1.4× 772 0.8× 172 8.8k
Robert A. McCutcheon United Kingdom 31 2.7k 1.7× 1.3k 1.0× 1.5k 1.3× 1.3k 1.2× 715 0.7× 118 6.4k
Wolfgang Maier Germany 49 2.3k 1.4× 688 0.5× 1.3k 1.2× 1.1k 1.1× 612 0.6× 172 7.1k
Hiroaki Hori Japan 38 1.1k 0.7× 1.1k 0.8× 1.0k 0.9× 667 0.6× 346 0.4× 157 5.0k
Thomas C. Baghai Germany 45 1.3k 0.8× 1.5k 1.1× 839 0.7× 1.3k 1.2× 1.2k 1.2× 170 6.7k
Jonathan Savitz United States 48 2.2k 1.4× 2.6k 1.9× 1.9k 1.7× 989 0.9× 713 0.7× 131 7.5k

Countries citing papers authored by Yiru Fang

Since Specialization
Citations

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

Fields of papers citing papers by Yiru Fang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yiru Fang

This figure shows the co-authorship network connecting the top 25 collaborators of Yiru Fang. A scholar is included among the top collaborators of Yiru Fang 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 Yiru Fang. Yiru Fang 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.
Fang, Yiru, et al.. (2024). Arabidopsis HAPLESS13/AP-1µ is critical for pollen sac formation and tapetal function. Plant Science. 341. 111998–111998. 3 indexed citations
2.
Wu, Zhiguo, Jun Wang, Chen Zhang, et al.. (2024). Clinical distinctions in symptomatology and psychiatric comorbidities between misdiagnosed bipolar I and bipolar II disorder versus major depressive disorder. BMC Psychiatry. 24(1). 352–352. 5 indexed citations
4.
Zhu, Yuncheng, Zhiguo Wu, Dongmei Zhao, et al.. (2023). Clinical Guideline (CANMAT 2016) Discordance of Medications for Patients with Major Depressive Disorder in China. Neuropsychiatric Disease and Treatment. Volume 19. 829–839. 1 indexed citations
5.
Shi, Yifan, Chen Zhang, David Mellor, et al.. (2023). Characteristics and symptomatology of major depressive disorder with atypical features from symptom to syndromal level. Journal of Affective Disorders. 333. 249–256. 1 indexed citations
6.
Li, Ming, Tao Li, Xiao Xiao, et al.. (2022). Phenotypes, mechanisms and therapeutics: insights from bipolar disorder GWAS findings. Molecular Psychiatry. 27(7). 2927–2939. 17 indexed citations
7.
Zhu, Yuncheng, Xiaohui Wu, Hongmei Liu, et al.. (2022). Employing biochemical biomarkers for building decision tree models to predict bipolar disorder from major depressive disorder. Journal of Affective Disorders. 308. 190–198. 15 indexed citations
8.
Yang, Tao, Sophia Frangou, Raymond W. Lam, et al.. (2021). Probing the clinical and brain structural boundaries of bipolar and major depressive disorder. Translational Psychiatry. 11(1). 48–48. 12 indexed citations
9.
Wu, Xiaohui, Yuncheng Zhu, Yifan Shi, et al.. (2021). Peripheral biomarkers to predict the diagnosis of bipolar disorder from major depressive disorder in adolescents. European Archives of Psychiatry and Clinical Neuroscience. 272(5). 817–826. 23 indexed citations
10.
Yang, Lu, Zhiguo Wu, Lan Cao, et al.. (2021). Predictors and moderators of quality of life in patients with major depressive disorder: An AGTs-MDD study report. Journal of Psychiatric Research. 138. 96–102. 4 indexed citations
11.
Wang, Fan, Yiming Chen, Dongbin Lyu, et al.. (2021). Difference in the regulation of biological rhythm symptoms of Major depressive disorder between escitalopram and mirtazapine. Journal of Affective Disorders. 296. 258–264. 4 indexed citations
12.
Fang, Yiru & Ruizhi Mao. (2019). Introduction. Advances in experimental medicine and biology. 1180. 1–17. 4 indexed citations
13.
14.
Zhou, Rubai, Fan Wang, Guoqing Zhao, et al.. (2018). Effects of tumor necrosis factor-α polymorphism on the brain structural changes of the patients with major depressive disorder. Translational Psychiatry. 8(1). 217–217. 30 indexed citations
15.
Hu, Yingyan, Wu Hong, Alicia K. Smith, et al.. (2017). Association analysis between mitogen-activated protein/extracellular signal-regulated kinase (MEK) gene polymorphisms and depressive disorder in the Han Chinese population. Journal of Affective Disorders. 222. 120–125. 6 indexed citations
16.
Zhang, Chen, Dengfeng Zhang, Zhiguo Wu, et al.. (2016). Complement factor H and susceptibility to major depressive disorder in Han Chinese. The British Journal of Psychiatry. 208(5). 446–452. 23 indexed citations
17.
Fang, Yiru, et al.. (2016). Perceptions of stigma and its correlates among patients with major depressive disorder: A multicenter survey from China. Asia-Pacific Psychiatry. 9(3). 11 indexed citations
18.
Hong, Wu, Jinbo Fan, Chengmei Yuan, et al.. (2014). Significantly decreased mRNA levels of BDNF and MEK1 genes in treatment-resistant depression. Neuroreport. 25(10). 753–755. 29 indexed citations
19.
Yang, Haichen, Yu‐Tao Xiang, Tiebang Liu, et al.. (2012). Hypomanic symptoms assessed by the HCL-32 in patients with major depressive disorder: A multicenter trial across China. Journal of Affective Disorders. 143(1-3). 203–207. 19 indexed citations
20.
Wang, Zuowei, David E. Kemp, Philip K. Chan, et al.. (2010). Comparisons of the tolerability and sensitivity of quetiapine-XR in the acute treatment of schizophrenia, bipolar mania, bipolar depression, major depressive disorder, and generalized anxiety disorder. The International Journal of Neuropsychopharmacology. 14(1). 131–142. 17 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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