Shuxiong Wang

802 total citations
8 papers, 403 citations indexed

About

Shuxiong Wang is a scholar working on Molecular Biology, Oncology and Biophysics. According to data from OpenAlex, Shuxiong Wang has authored 8 papers receiving a total of 403 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 5 papers in Oncology and 2 papers in Biophysics. Recurrent topics in Shuxiong Wang's work include Single-cell and spatial transcriptomics (7 papers), Cancer Cells and Metastasis (5 papers) and Gene Regulatory Network Analysis (3 papers). Shuxiong Wang is often cited by papers focused on Single-cell and spatial transcriptomics (7 papers), Cancer Cells and Metastasis (5 papers) and Gene Regulatory Network Analysis (3 papers). Shuxiong Wang collaborates with scholars based in United States and China. Shuxiong Wang's co-authors include Qing Nie, Adam L. MacLean, Peijie Zhou, Yutong Sha, Tiejun Li, Scott X. Atwood, Christian F. Guerrero‐Juarez, Michael L. Drummond, Adam R. Stabell and Stephanie Wu and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and Science Advances.

In The Last Decade

Shuxiong Wang

7 papers receiving 402 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Shuxiong Wang United States	7	283	87	64	64	53	8	403
Peter W. Krenn Austria	10	286 1.0×	58 0.7×	24 0.4×	126 2.0×	39 0.7×	18	472
R. Hein Germany	10	290 1.0×	189 2.2×	10 0.2×	116 1.8×	85 1.6×	11	486
Margarete Schön Germany	8	157 0.6×	146 1.7×	11 0.2×	138 2.2×	36 0.7×	8	399
Karin M. Greulich‐Bode Germany	13	351 1.2×	86 1.0×	31 0.5×	59 0.9×	61 1.2×	20	521
Kelly Mitchell United States	10	212 0.7×	67 0.8×	8 0.1×	89 1.4×	55 1.0×	13	379
Olivia B. Harris United Kingdom	6	176 0.6×	190 2.2×	49 0.8×	43 0.7×	52 1.0×	7	313
Bridget Finnerty United States	6	212 0.7×	169 1.9×	10 0.2×	41 0.6×	78 1.5×	7	379
Gergő Kiszner Hungary	10	185 0.7×	85 1.0×	17 0.3×	32 0.5×	46 0.9×	13	373
Johannes Bagnoli Germany	8	225 0.8×	26 0.3×	16 0.3×	71 1.1×	55 1.0×	12	318
Andrew Muinonen‐Martin United Kingdom	8	102 0.4×	85 1.0×	12 0.2×	63 1.0×	14 0.3×	11	315

Countries citing papers authored by Shuxiong Wang

Since Specialization

Citations

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

Fields of papers citing papers by Shuxiong Wang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shuxiong Wang

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

All Works

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8 of 8 papers shown

1.

Wang, Shuxiong, Christina Tu, Quy Nguyen, et al.. (2025). Sequential emergence and contraction of epithelial subtypes in the prenatal human choroid plexus revealed by a stem cell model. Nature Communications. 16(1). 5149–5149.

2.

Stabell, Adam R., Grace E. Lee, Yunlong Jia, et al.. (2023). Single-cell transcriptomics of human-skin-equivalent organoids. Cell Reports. 42(5). 112511–112511. 14 indexed citations

3.

Guerrero‐Juarez, Christian F., Shuxiong Wang, Yutong Sha, et al.. (2022). Single-cell analysis of human basal cell carcinoma reveals novel regulators of tumor growth and the tumor microenvironment. Science Advances. 8(23). eabm7981–eabm7981. 26 indexed citations

4.

Zhou, Peijie, Shuxiong Wang, Tiejun Li, & Qing Nie. (2021). Dissecting transition cells from single-cell transcriptome data through multiscale stochastic dynamics. Nature Communications. 12(1). 5609–5609. 58 indexed citations

5.

Sha, Yutong, Shuxiong Wang, Federico Bocci, Peijie Zhou, & Qing Nie. (2021). Inference of Intercellular Communications and Multilayer Gene-Regulations of Epithelial–Mesenchymal Transition From Single-Cell Transcriptomic Data. Frontiers in Genetics. 11. 604585–604585. 22 indexed citations

6.

Wang, Shuxiong, Michael L. Drummond, Christian F. Guerrero‐Juarez, et al.. (2020). Single cell transcriptomics of human epidermis identifies basal stem cell transition states. Nature Communications. 11(1). 4239–4239. 135 indexed citations

7.

Sha, Yutong, Shuxiong Wang, Peijie Zhou, & Qing Nie. (2020). Inference and multiscale model of epithelial-to-mesenchymal transition via single-cell transcriptomic data. Nucleic Acids Research. 48(17). 9505–9520. 45 indexed citations

8.

Wang, Shuxiong, et al.. (2019). Cell lineage and communication network inference via optimization for single-cell transcriptomics. Nucleic Acids Research. 47(11). e66–e66. 103 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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