Shu Ran

695 total citations
20 papers, 233 citations indexed

About

Shu Ran is a scholar working on Genetics, Molecular Biology and Pathology and Forensic Medicine. According to data from OpenAlex, Shu Ran has authored 20 papers receiving a total of 233 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Genetics, 8 papers in Molecular Biology and 3 papers in Pathology and Forensic Medicine. Recurrent topics in Shu Ran's work include Genetic Associations and Epidemiology (13 papers), Genetic and phenotypic traits in livestock (5 papers) and Genomic variations and chromosomal abnormalities (4 papers). Shu Ran is often cited by papers focused on Genetic Associations and Epidemiology (13 papers), Genetic and phenotypic traits in livestock (5 papers) and Genomic variations and chromosomal abnormalities (4 papers). Shu Ran collaborates with scholars based in China, United States and Hong Kong. Shu Ran's co-authors include Yu‐Fang Pei, Lei Zhang, Rong Hai, Hong‐Wen Deng, Hui Shen, Yong Lin, Christopher J. Papasian, Qiuying Tian, Xue-Zhen Zhu and Qing Tian and has published in prestigious journals such as PLoS ONE, Scientific Reports and Human Molecular Genetics.

In The Last Decade

Shu Ran

20 papers receiving 228 citations

Peers

Shu Ran

GENET

PHYSI

OSM

RHEUM

Zhaotong Lin United States

Hou-Feng Zheng Canada

Vedia Tonyukuk Türkiye

Thaís Kataoka Homma Brazil

Lúcia Helena Coelho Nóbrega Brazil

Steven J Bailey United Kingdom

Tine Tesovnik Slovenia

Wagner Antonio da Rosa Baratela Brazil

Erin Santa United States

M Pura Slovakia

Zhaotong Lin United States

Shu Ran

136 ×1.1

GENET

95 ×0.9

29 ×0.5

PHYSI

5 ×0.2

OSM

21 ×0.9

RHEUM

Citations per year, relative to Shu Ran Shu Ran (= 1×) peers Zhaotong Lin

Countries citing papers authored by Shu Ran

Since Specialization

Citations

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

Fields of papers citing papers by Shu Ran

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shu Ran

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

All Works

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20 of 20 papers shown

Ran, Shu, et al.. (2025). Multi-trait Genome-Wide Analysis Identified 20 Novel Loci for Sarcopenia-Related Traits in UK Biobank. Calcified Tissue International. 116(1). 10–10. 1 indexed citations

Ran, Shu, et al.. (2023). Associations of appendicular lean mass and walking pace with hypertension: a two-sample Mendelian randomization study. Journal of Hypertension. 41(8). 1347–1348. 1 indexed citations

Ran, Shu, et al.. (2021). Metabolic Regulator IAPP (Amylin) Is Required for BRAF and RAS Oncogene-Induced Senescence. Molecular Cancer Research. 19(5). 874–885. 2 indexed citations

Ran, Shu, Yuxue Zhang, Lei Zhang, et al.. (2020). Whole‐exome sequencing and genome‐wide association studies identify novel sarcopenia risk genes in Han Chinese. Molecular Genetics & Genomic Medicine. 8(8). e1267–e1267. 7 indexed citations

Ran, Shu, Yuxue Zhang, Lu Liu, et al.. (2020). Association of 3p27.1 Variants with Whole Body Lean Mass Identified by a Genome-wide Association Study. Scientific Reports. 10(1). 4293–4293. 2 indexed citations

Ran, Shu, Yuxue Zhang, Lei Zhang, et al.. (2020). Replication of FTO Gene associated with lean mass in a Meta-Analysis of Genome-Wide Association Studies. Scientific Reports. 10(1). 5057–5057. 19 indexed citations

Zhang, Yuxue, Shanshan Zhang, Shu Ran, et al.. (2020). Three pleiotropic loci associated with bone mineral density and lean body mass. Molecular Genetics and Genomics. 296(1). 55–65. 5 indexed citations

Liu, Lu, Yu‐Fang Pei, Xiaolin Yang, et al.. (2019). Identification of a 1p21 independent functional variant for abdominal obesity. International Journal of Obesity. 43(12). 2480–2490. 4 indexed citations

Pei, Yu‐Fang, Lu Liu, Xiaolin Yang, et al.. (2019). Joint Association Analysis Identified 18 New Loci for Bone Mineral Density. Journal of Bone and Mineral Research. 34(6). 1086–1094. 24 indexed citations

10.

Ran, Shu, Lei Zhang, Lu Liu, et al.. (2017). Gene-based genome-wide association study identified 19p13.3 for lean body mass. Scientific Reports. 7(1). 45025–45025. 3 indexed citations

11.

Pei, Yu‐Fang, Rong Hai, Xiuyan Wang, et al.. (2016). Genome-wide association meta-analyses identified 1q43 and 2q32.2 for hip Ward's triangle areal bone mineral density. Bone. 91. 1–10. 10 indexed citations

12.

Pei, Yu‐Fang, Zonggang Xie, Weiwei Hu, et al.. (2016). Association of 3q13.32 variants with hip trochanter and intertrochanter bone mineral density identified by a genome-wide association study. Osteoporosis International. 27(11). 3343–3354. 8 indexed citations

13.

Zhang, Lei, Yueping Shen, Shu Ran, et al.. (2015). A new method for estimating effect size distribution and heritability from genome-wide association summary results. Human Genetics. 135(2). 171–184. 6 indexed citations

14.

Ran, Shu, Yongjun Liu, Lei Zhang, et al.. (2014). Genome-Wide Association Study Identified Copy Number Variants Important for Appendicular Lean Mass. PLoS ONE. 9(3). e89776–e89776. 9 indexed citations

15.

Zhang, Yan, Yoseph Asmelash Gebru, Xi Chen, et al.. (2013). Effects of angiotensin II type 1 receptor blocker on bones in mice with type 1 diabetes induced by streptozotocin. Journal of the Renin-Angiotensin-Aldosterone System. 15(3). 218–227. 18 indexed citations

16.

Pei, Yu‐Fang, Lei Zhang, Yong Liu, et al.. (2013). Meta-analysis of genome-wide association data identifies novel susceptibility loci for obesity. Human Molecular Genetics. 23(3). 820–830. 62 indexed citations

17.

Ran, Shu, Yu‐Fang Pei, Yong-Jun Liu, et al.. (2013). Bivariate Genome-Wide Association Analyses Identified Genes with Pleiotropic Effects for Femoral Neck Bone Geometry and Age at Menarche. PLoS ONE. 8(4). e60362–e60362. 12 indexed citations

18.

Pei, Yu‐Fang, Lei Zhang, Tie‐Lin Yang, et al.. (2012). Genome-Wide Association Study of Copy Number Variants Suggests LTBP1 and FGD4 Are Important for Alcohol Drinking. PLoS ONE. 7(1). e30860–e30860. 10 indexed citations

19.

Hai, Rong, Lei Zhang, Yu‐Fang Pei, et al.. (2012). Bivariate genome-wide association study suggests that the DARC gene influences lean body mass and age at menarche. Science China Life Sciences. 55(6). 516–520. 7 indexed citations

20.

Hai, Rong, Yu‐Fang Pei, Hui Shen, et al.. (2011). Genome-wide association study of copy number variation identified gremlin1 as a candidate gene for lean body mass. Journal of Human Genetics. 57(1). 33–37. 23 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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