Sijia Wang

4.3k total citations
114 papers, 1.5k citations indexed

About

Sijia Wang is a scholar working on Molecular Biology, Genetics and Cell Biology. According to data from OpenAlex, Sijia Wang has authored 114 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Molecular Biology, 28 papers in Genetics and 16 papers in Cell Biology. Recurrent topics in Sijia Wang's work include Genetic Associations and Epidemiology (13 papers), Skin Protection and Aging (11 papers) and Epigenetics and DNA Methylation (11 papers). Sijia Wang is often cited by papers focused on Genetic Associations and Epidemiology (13 papers), Skin Protection and Aging (11 papers) and Epigenetics and DNA Methylation (11 papers). Sijia Wang collaborates with scholars based in China, United States and United Kingdom. Sijia Wang's co-authors include Jin Li, Yajun Yang, Jean Krutmann, Tamara Schikowski, Anke Hüls, Mary S. Matsui, Andrea Vierkötter, Anan Ding, Jingze Tan and Hu Liu and has published in prestigious journals such as Nature Communications, Nature Genetics and SHILAP Revista de lepidopterología.

In The Last Decade

Sijia Wang

105 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sijia Wang China 22 417 288 174 157 150 114 1.5k
Arne Dahlback Norway 30 188 0.5× 687 2.4× 96 0.6× 181 1.2× 541 3.6× 77 2.9k
Ian Laing United Kingdom 37 491 1.2× 170 0.6× 247 1.4× 154 1.0× 95 0.6× 173 5.1k
Takechiyo Yamada Japan 28 596 1.4× 199 0.7× 60 0.3× 78 0.5× 95 0.6× 147 2.8k
Takayoshi Ikeda Japan 23 546 1.3× 46 0.2× 165 0.9× 49 0.3× 135 0.9× 108 2.8k
Jack Green United States 27 1.5k 3.5× 219 0.8× 228 1.3× 134 0.9× 27 0.2× 68 2.7k
G. Kistler Switzerland 12 594 1.4× 102 0.4× 138 0.8× 179 1.1× 85 0.6× 37 2.4k
R F McMahon United Kingdom 28 511 1.2× 36 0.1× 232 1.3× 97 0.6× 101 0.7× 112 2.5k
Di Wu China 27 985 2.4× 162 0.6× 232 1.3× 102 0.6× 318 2.1× 156 2.7k
Mustafa Turan Türkiye 25 282 0.7× 77 0.3× 180 1.0× 207 1.3× 23 0.2× 112 1.8k
Hee Jeong Kim South Korea 34 1.1k 2.6× 55 0.2× 288 1.7× 78 0.5× 54 0.4× 232 3.5k

Countries citing papers authored by Sijia Wang

Since Specialization
Citations

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

Fields of papers citing papers by Sijia Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sijia Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Sijia Wang. A scholar is included among the top collaborators of Sijia Wang 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 Sijia Wang. Sijia Wang 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.
Zhang, Zhao, Mu Li, Jingze Tan, et al.. (2025). FPQuant: A deep learning-based scalable framework for fingerprint phenomics quantification in large-scale biometric population studies. Pattern Recognition. 173. 112808–112808.
2.
Xia, Mingfeng, Yuxiang Dai, Qingxia Huang, et al.. (2025). Cross-ancestry analyses of Chinese and European populations reveal insights into the genetic architecture and disease implication of metabolites. Cell Genomics. 5(4). 100810–100810. 2 indexed citations
3.
4.
Xiong, Ziyi, Yi Li, Xianjing Liu, et al.. (2025). Combined genome-wide association study of facial traits in Europeans increases explained variance and improves prediction. Nature Communications. 16(1). 6562–6562. 2 indexed citations
5.
Wang, Linxiao, et al.. (2024). Comparative analysis of models in predicting the effects of SNPs on TF-DNA binding using large-scale in vitro and in vivo data. Briefings in Bioinformatics. 25(2). 1 indexed citations
6.
Peng, Yanmin, Chao Chai, Kaizhong Xue, et al.. (2024). Unraveling multi‐scale neuroimaging biomarkers and molecular foundations for schizophrenia: A combined multivariate pattern analysis and transcriptome‐neuroimaging association study. CNS Neuroscience & Therapeutics. 30(8). e14906–e14906. 2 indexed citations
7.
8.
Faber, Benjamin G, Monika Frysz, Huandong Lin, et al.. (2024). The genetic architecture of hip shape and its role in the development of hip osteoarthritis and fracture. Human Molecular Genetics. 34(3). 207–217. 3 indexed citations
9.
Wu, Sijie, Min Zhang, Jinxi Li, et al.. (2023). Scalp hair loss is not random across follicular units: A new insight into human hair ageing. International Journal of Cosmetic Science. 45(4). 548–555. 1 indexed citations
10.
Liu, Hongmei, Tingting Li, Song Zhao, et al.. (2023). Restoring carboxypeptidase E rescues BDNF maturation and neurogenesis in aged brains. PubMed. 2(2). lnad015–lnad015. 5 indexed citations
11.
Urbánek, Pavel, Sijia Wang, Mara Sannai, et al.. (2023). Poly(ADP-Ribose) Polymerase-1 Lacking Enzymatic Activity Is Not Compatible with Mouse Development. Cells. 12(16). 2078–2078. 8 indexed citations
12.
Frysz, Monika, Benjamin G Faber, Huandong Lin, et al.. (2023). Comparison between UK Biobank and Shanghai Changfeng suggests distinct hip morphology may contribute to ethnic differences in the prevalence of hip osteoarthritis. Osteoarthritis and Cartilage. 33(4). 473–481. 4 indexed citations
13.
Peng, Qianqian, Yu Liu, Canfeng Zhang, et al.. (2022). Genetic Variants in Telomerase Reverse Transcriptase Contribute to Solar Lentigines. Journal of Investigative Dermatology. 143(6). 1062–1072.e25. 3 indexed citations
14.
Su, Qian, Yingchao Song, Qing‐Qing Yang, et al.. (2022). Brain-activation-based individual identification reveals individually unique activation patterns elicited by pain and touch. NeuroImage. 260. 119436–119436. 9 indexed citations
15.
Yang, Keyan, Song Zhao, Jiaqi Shen, et al.. (2022). Ca2+ homeostasis maintained by TMCO1 underlies corpus callosum development via ERK signaling. Cell Death and Disease. 13(8). 674–674. 6 indexed citations
16.
Chen, Kitty Jieyi, Ping Zhang, Bo Liu, et al.. (2022). An additional whole-exome sequencing study in 102 panel-undiagnosed patients: A retrospective study in a Chinese craniosynostosis cohort. Frontiers in Genetics. 13. 967688–967688. 2 indexed citations
17.
Huang, Xin, Sijia Wang, Jin Li, & Yungang He. (2021). Dissecting dynamics and differences of selective pressures in the evolution of human pigmentation. Biology Open. 10(2). 5 indexed citations
18.
Luo, Qi, Yan Chen, Yu Liu, et al.. (2021). A Genome-Wide Scan on Individual Typology Angle Found Variants at SLC24A2 Associated with Skin Color Variation in Chinese Populations. Journal of Investigative Dermatology. 142(4). 1223–1227.e14. 10 indexed citations
19.
Zhou, Yuxun, Tong Li, Maochun Wang, et al.. (2018). miR-505-3p is a repressor of puberty onset in female mice. Journal of Endocrinology. 240(3). 379–392. 10 indexed citations
20.
Wang, Sijia, et al.. (2018). Isolation and identification of symbiotic fungi in Eucalyptus roots.. Xibei zhiwu xuebao. 38(8). 1553–1561. 1 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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