Young Tang

512 total citations
20 papers, 254 citations indexed

About

Young Tang is a scholar working on Molecular Biology, Genetics and Animal Science and Zoology. According to data from OpenAlex, Young Tang has authored 20 papers receiving a total of 254 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 6 papers in Genetics and 5 papers in Animal Science and Zoology. Recurrent topics in Young Tang's work include Pluripotent Stem Cells Research (10 papers), CRISPR and Genetic Engineering (9 papers) and Animal Virus Infections Studies (5 papers). Young Tang is often cited by papers focused on Pluripotent Stem Cells Research (10 papers), CRISPR and Genetic Engineering (9 papers) and Animal Virus Infections Studies (5 papers). Young Tang collaborates with scholars based in United States, China and Japan. Young Tang's co-authors include Yue Su, Ling Wang, Chang Huang, Jiaqi Zhu, Alexander L. Chu, Xiuchun Tian, Ming Zhang, Antonio E. Garmendia, Denzil Bernard and Zongliang Jiang and has published in prestigious journals such as Journal of Biological Chemistry, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Young Tang

17 papers receiving 251 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Young Tang United States	11	156	68	45	41	25	20	254
Xiaodong Zou China	10	209 1.3×	166 2.4×	69 1.5×	53 1.3×	40 1.6×	14	353
Nai-Yun Hsu United States	5	164 1.1×	51 0.8×	14 0.3×	27 0.7×	16 0.6×	5	266
Jian Cheng China	10	148 0.9×	145 2.1×	66 1.5×	12 0.3×	10 0.4×	39	346
Scott E. Diamond United States	11	258 1.7×	67 1.0×	31 0.7×	68 1.7×	8 0.3×	12	411
Julen Rodríguez-Castejón Spain	7	230 1.5×	71 1.0×	17 0.4×	40 1.0×	7 0.3×	13	295
Itziar Gómez-Aguado Spain	8	235 1.5×	75 1.1×	17 0.4×	40 1.0×	7 0.3×	10	308
Maia Segura‐Wang Germany	7	146 0.9×	84 1.2×	51 1.1×	10 0.2×	8 0.3×	14	268
Andrew S. Mason United Kingdom	9	107 0.7×	78 1.1×	28 0.6×	10 0.2×	27 1.1×	22	229
Asako Shigeno Japan	6	161 1.0×	23 0.3×	24 0.5×	105 2.6×	15 0.6×	9	328

Countries citing papers authored by Young Tang

Since Specialization

Citations

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

Fields of papers citing papers by Young Tang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Young Tang

This figure shows the co-authorship network connecting the top 25 collaborators of Young Tang. A scholar is included among the top collaborators of Young Tang 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 Young Tang. Young Tang 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

Wang, Yifei, Jing Yang, Kai Wang, et al.. (2025). AnimalGWASAtlas: Annotation and prioritization of GWAS loci and quantitative trait loci for animal complex traits. Journal of Biological Chemistry. 301(3). 108267–108267. 1 indexed citations

Zhang, Su, Weitao Hu, Young Tang, & Xiaoqing Chen. (2025). Identification and validation of key autophagy-related genes in lupus nephritis by bioinformatics and machine learning. PLoS ONE. 20(1). e0318280–e0318280.

Zou, Guijin, et al.. (2025). Signal-induced NLRP3 phase separation initiates inflammasome activation. Cell Research. 35(6). 437–452. 14 indexed citations

Gan, Mailin, Xingyu Wang, Young Tang, et al.. (2024). Whole transcriptome sequencing analysis reveals the effect of circZFYVE9/miR-378a-3p/IMMT axis on mitochondrial function in adipocytes. International Journal of Biological Macromolecules. 281(Pt 2). 136916–136916.

Dash, Radha Charan, Shuangshuang Guo, Yue Su, et al.. (2024). Discovery of small molecules against porcine reproductive and respiratory syndrome virus replication by targeting NendoU activity. Journal of Virology. 99(2). e0203424–e0203424.

Bernard, Denzil, Jianing Shen, Yue Su, et al.. (2023). Identification of New Compounds against PRRSV Infection by Directly Targeting CD163. Journal of Virology. 97(5). e0005423–e0005423. 18 indexed citations

Su, Yue, et al.. (2022). Disrupting ACE2 Dimerization Mitigates the Infection by SARS-CoV-2 Pseudovirus. SHILAP Revista de lepidopterología. 2. 5 indexed citations

Su, Yue, Ling Wang, Zhiqiang Fan, et al.. (2021). Establishment of Bovine-Induced Pluripotent Stem Cells. International Journal of Molecular Sciences. 22(19). 10489–10489. 27 indexed citations

Huang, Chang, Denzil Bernard, Radha Charan Dash, et al.. (2020). Small molecules block the interaction between porcine reproductive and respiratory syndrome virus and CD163 receptor and the infection of pig cells. Virology Journal. 17(1). 116–116. 37 indexed citations

10.

Huang, Chang, et al.. (2020). Cryptotanshinone protects porcine alveolar macrophages from infection with porcine reproductive and respiratory syndrome virus. Antiviral Research. 183. 104937–104937. 11 indexed citations

11.

Su, Yue, et al.. (2020). Induced pluripotent stem cells from farm animals. Journal of Animal Science. 98(11). 26 indexed citations

12.

Wang, Ling, Yue Su, Chang Huang, et al.. (2019). FOXH1 Is Regulated by NANOG and LIN28 for Early-stage Reprogramming. Scientific Reports. 9(1). 16443–16443. 14 indexed citations

13.

Wang, Ling, et al.. (2019). NANOG and LIN28 dramatically improve human cell reprogramming by modulating LIN41 and canonical WNT activities. Biology Open. 8(12). 30 indexed citations

14.

Wang, Ling, Neil C. Talbot, Chang Huang, et al.. (2018). Analyzing bovine OCT4 and NANOG enhancer activity in pluripotent stem cells using fluorescent protein reporters. PLoS ONE. 13(10). e0203923–e0203923. 2 indexed citations

15.

Wang, Ling, Zongliang Jiang, Jingyue Duan, et al.. (2018). JAK/STAT3 regulated global gene expression dynamics during late-stage reprogramming process. BMC Genomics. 19(1). 183–183. 17 indexed citations

16.

Wang, Ling, et al.. (2017). Enhanced human somatic cell reprogramming efficiency by fusion of the MYC transactivation domain and OCT4. Stem Cell Research. 25. 88–97. 10 indexed citations

17.

Wang, Ling, Jingyue Duan, Chang Huang, et al.. (2017). LIF activated Jak signaling determines Esrrb expression during late-stage reprogramming. Biology Open. 7(1). 9 indexed citations

18.

Wang, Ling, Zongliang Jiang, Yan Luo, et al.. (2017). Akt3 is responsible for the survival and proliferation of embryonic stem cells. Biology Open. 6(6). 850–861. 28 indexed citations

19.

Talbot, Neil C., Ling Wang, Wesley M. Garrett, Thomas J. Caperna, & Young Tang. (2015). Establishment and characterization of feeder cell-dependent bovine fetal liver cell lines. In Vitro Cellular & Developmental Biology - Animal. 52(3). 314–326. 3 indexed citations

20.

Tang, Young, et al.. (2012). 278 Jak/Stat3 SIGNALING PROMOTES SOMATIC CELL REPROGRAMMING BY EPIGENETIC REGULATION. Reproduction Fertility and Development. 25(1). 287–287. 2 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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