Shaoqiang Wang

780 total citations
30 papers, 557 citations indexed

About

Shaoqiang Wang is a scholar working on Molecular Biology, Cancer Research and Genetics. According to data from OpenAlex, Shaoqiang Wang has authored 30 papers receiving a total of 557 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 13 papers in Cancer Research and 7 papers in Genetics. Recurrent topics in Shaoqiang Wang's work include Cancer-related molecular mechanisms research (11 papers), RNA modifications and cancer (10 papers) and Genetic and phenotypic traits in livestock (5 papers). Shaoqiang Wang is often cited by papers focused on Cancer-related molecular mechanisms research (11 papers), RNA modifications and cancer (10 papers) and Genetic and phenotypic traits in livestock (5 papers). Shaoqiang Wang collaborates with scholars based in China, United States and Australia. Shaoqiang Wang's co-authors include Yuanda Cheng, Chaojun Duan, Wolong Zhou, Chunfang Zhang, Wei Chen, Lina Wang, Jun Wang, Sulai Liu, Li Wang and Liming Zhang and has published in prestigious journals such as PLoS ONE, Scientific Reports and Cellular and Molecular Life Sciences.

In The Last Decade

Shaoqiang Wang

29 papers receiving 552 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shaoqiang Wang China 15 384 275 81 73 57 30 557
Jun Chi China 9 388 1.0× 322 1.2× 76 0.9× 59 0.8× 44 0.8× 20 621
Zuozhen Yang China 10 363 0.9× 191 0.7× 72 0.9× 53 0.7× 48 0.8× 40 482
Jianting Mao China 7 312 0.8× 124 0.5× 38 0.5× 70 1.0× 39 0.7× 10 405
Emanuele Monteleone Italy 8 779 2.0× 540 2.0× 36 0.4× 87 1.2× 47 0.8× 10 929
Shida Zhu China 13 276 0.7× 162 0.6× 70 0.9× 99 1.4× 64 1.1× 37 484
Veronika I. Zabarovska Sweden 13 508 1.3× 146 0.5× 88 1.1× 98 1.3× 30 0.5× 19 635
Stefania Oliveto Italy 11 448 1.2× 271 1.0× 21 0.3× 52 0.7× 33 0.6× 18 629
Li-Juan Ji China 9 413 1.1× 212 0.8× 54 0.7× 53 0.7× 42 0.7× 10 495

Countries citing papers authored by Shaoqiang Wang

Since Specialization
Citations

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

Fields of papers citing papers by Shaoqiang Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shaoqiang Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Shaoqiang Wang. A scholar is included among the top collaborators of Shaoqiang 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 Shaoqiang Wang. Shaoqiang 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.
Wang, Yuhan, Nannan Han, Tong Shi, et al.. (2025). Mechanisms and applications of mesenchymal stem cell exosomes in enhancing fertility. Stem Cell Research & Therapy. 16(1). 588–588.
2.
Zhang, Liming, Shaoqiang Wang, & Lina Wang. (2024). Prognostic value and immunological function of cuproptosis-related genes in lung adenocarcinoma. Heliyon. 10(9). e30446–e30446. 5 indexed citations
3.
Zheng, Yingying, et al.. (2024). IGFBP2/ITGA5 promotes gefitinib resistance via activating STAT3/CXCL1 axis in non-small cell lung cancer. Cell Death and Disease. 15(6). 447–447. 11 indexed citations
4.
Song, Yan, Wei Wang, Shaoqiang Wang, et al.. (2023). Aberrant Dendritic Cell Subsets in Patients with Myasthenia Gravis and Related Clinical Features. NeuroImmunoModulation. 30(1). 69–80. 5 indexed citations
5.
Wang, Shaoqiang, Lina Wang, Hang Lin, et al.. (2023). LncRNA CALML3-AS1 modulated by m6A modification induces BTNL9 methylation to drive non-small-cell lung cancer progression. Cancer Gene Therapy. 30(12). 1649–1662. 10 indexed citations
6.
Zhang, Liming, Ling Zong, Wenhui Li, et al.. (2023). Construction of lncRNA prognostic model related to cuproptosis in esophageal carcinoma. Frontiers in Genetics. 14. 1120827–1120827. 6 indexed citations
7.
Zheng, Yingying, et al.. (2023). METTL14 promotes the development of diabetic kidney disease by regulating m6A modification of TUG1. Acta Diabetologica. 60(11). 1567–1580. 20 indexed citations
8.
Ma, Jiajun, Linfeng Li, Liming Zhang, et al.. (2023). LINC00963 promotes the malignancy and metastasis of lung adenocarcinoma by stabilizing Zeb1 and exosomes-induced M2 macrophage polarization. Molecular Medicine. 29(1). 1–1. 22 indexed citations
9.
Wang, Shaoqiang, Li Wang, Hang Lin, et al.. (2022). m6A methyltransferase METTL3-induced lncRNA SNHG17 promotes lung adenocarcinoma gefitinib resistance by epigenetically repressing LATS2 expression. Cell Death and Disease. 13(7). 657–657. 62 indexed citations
10.
Wang, Shaoqiang, et al.. (2022). svBreak: A New Approach for the Detection of Structural Variant Breakpoints Based on Convolutional Neural Network. BioMed Research International. 2022(1). 7196040–7196040. 1 indexed citations
11.
12.
Cheng, Yuanda, et al.. (2021). LncRNA UCC promotes epithelial–mesenchymal transition via the miR-143-3p/SOX5 axis in non-small-cell lung cancer. Laboratory Investigation. 101(9). 1153–1165. 18 indexed citations
13.
Zhang, Heng, Shaoqiang Wang, Chunfang Zhang, et al.. (2021). GRP78 facilitates M2 macrophage polarization and tumour progression. Cellular and Molecular Life Sciences. 78(23). 7709–7732. 29 indexed citations
14.
Zhou, Wolong, Yang Gao, Yuanda Cheng, et al.. (2020). MICAL2 is a novel nucleocytoplasmic shuttling protein promoting cancer invasion and growth of lung adenocarcinoma. Cancer Letters. 483. 75–86. 32 indexed citations
15.
Sun, Ting, Shaoqiang Wang, Ruihua Dang, et al.. (2019). Multiple domestication of swamp buffalo in China and South East Asia. Journal of Animal Breeding and Genetics. 137(3). 331–340. 14 indexed citations
16.
Chen, Wei, Jun Wang, Sulai Liu, et al.. (2016). MicroRNA-361-3p suppresses tumor cell proliferation and metastasis by directly targeting SH2B1 in NSCLC. Journal of Experimental & Clinical Cancer Research. 35(1). 76–76. 77 indexed citations
17.
Wang, Shaoqiang & Qirong Wang. (2016). Clinical effects of probiotics in prevention of neonatal necrotizing enterocolitis. World Chinese Journal of Digestology. 24(15). 2406–2406. 1 indexed citations
18.
Li, Ran, Donghua Liu, Shaoqiang Wang, et al.. (2013). Single nucleotide polymorphisms of myostatin gene in Chinese domestic horses. Gene. 538(1). 150–154. 13 indexed citations
19.
Li, Ran, Shaoqiang Wang, Ruihua Dang, et al.. (2013). Y chromosome diversity and paternal origin of Chinese cattle. Molecular Biology Reports. 40(12). 6633–6636. 9 indexed citations
20.
Zhang, Hang, Chaojun Duan, Wei Chen, et al.. (2012). Clinical Significance of SH2B1 Adaptor Protein Expression in Non-small Cell Lung Cancer. Asian Pacific Journal of Cancer Prevention. 13(5). 2355–2362. 12 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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