Shangbin Yang

1.3k total citations
36 papers, 864 citations indexed

About

Shangbin Yang is a scholar working on Immunology, Molecular Biology and Genetics. According to data from OpenAlex, Shangbin Yang has authored 36 papers receiving a total of 864 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Immunology, 12 papers in Molecular Biology and 8 papers in Genetics. Recurrent topics in Shangbin Yang's work include Complement system in diseases (14 papers), Coagulation, Bradykinin, Polyphosphates, and Angioedema (7 papers) and Renal Diseases and Glomerulopathies (5 papers). Shangbin Yang is often cited by papers focused on Complement system in diseases (14 papers), Coagulation, Bradykinin, Polyphosphates, and Angioedema (7 papers) and Renal Diseases and Glomerulopathies (5 papers). Shangbin Yang collaborates with scholars based in United States, China and United Kingdom. Shangbin Yang's co-authors include Haifeng Wu, Spero R. Cataland, Ningzhi Xu, Hongxia Zhu, Susan Geyer, Lanping Quan, Jinfeng Bai, Shuang Yan, Yihua Wang and V. Michael Holers and has published in prestigious journals such as Blood, PLoS ONE and Cellular and Molecular Life Sciences.

In The Last Decade

Shangbin Yang

33 papers receiving 849 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shangbin Yang United States 18 406 294 213 211 131 36 864
Christine Payré France 17 193 0.5× 411 1.4× 450 2.1× 66 0.3× 50 0.4× 32 1.1k
Yuji Hori Japan 14 146 0.4× 581 2.0× 54 0.3× 78 0.4× 52 0.4× 31 925
Ryoko Harada Canada 16 235 0.6× 528 1.8× 31 0.1× 92 0.4× 40 0.3× 25 884
Jun Mori United Kingdom 16 305 0.8× 370 1.3× 38 0.2× 529 2.5× 125 1.0× 18 1.1k
J. Mark Hexham United States 16 262 0.6× 467 1.6× 44 0.2× 39 0.2× 14 0.1× 25 1.1k
David Bastian United States 20 591 1.5× 295 1.0× 10 0.0× 380 1.8× 82 0.6× 42 1.0k
Christa Pfeifhofer‐Obermair Austria 19 504 1.2× 433 1.5× 8 0.0× 128 0.6× 101 0.8× 31 1.1k
Kazuto Togitani Japan 13 93 0.2× 474 1.6× 10 0.0× 248 1.2× 80 0.6× 30 892
Haley E. Ramsey United States 17 149 0.4× 464 1.6× 10 0.0× 335 1.6× 79 0.6× 36 798
Suk-Ran Yoon South Korea 11 223 0.5× 270 0.9× 58 0.3× 42 0.2× 15 0.1× 12 573

Countries citing papers authored by Shangbin Yang

Since Specialization
Citations

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

Fields of papers citing papers by Shangbin Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shangbin Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Shangbin Yang. A scholar is included among the top collaborators of Shangbin Yang 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 Shangbin Yang. Shangbin Yang 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.
2.
Evans, Michael D., Shangbin Yang, Senthil Sukumar, et al.. (2025). Multicenter Prospective Pilot Study Identifying Thrombomodulin as a Potential Biomarker for Neurocognitive Outcomes in Immune Thrombotic Thrombocytopenic Purpura. Journal of Clinical Medicine. 14(3). 694–694.
3.
Yang, Shangbin, S.Y. Ma, Qiang Wang, et al.. (2025). Efficient Deployment of Peanut Leaf Disease Detection Models on Edge AI Devices. Agriculture. 15(3). 332–332. 2 indexed citations
4.
Song, Yingqiu, Jing Su, Shangbin Yang, et al.. (2024). PUF60 Promotes Chemoresistance Through Drug Efflux and Reducing Apoptosis in Gastric Cancer. International Journal of Medical Sciences. 22(2). 269–282. 2 indexed citations
5.
Song, Yingqiu, et al.. (2023). Identification of LSM family members as potential chemoresistance predictive and therapeutic biomarkers for gastric cancer. Frontiers in Oncology. 13. 1119945–1119945. 9 indexed citations
6.
Yang, Shangbin, et al.. (2023). Nrf2 enhances the therapeutic efficiency of adipose-derived stem cells in the treatment of neurogenic erectile dysfunction in a rat model. Basic and Clinical Andrology. 33(1). 39–39. 2 indexed citations
7.
Evans, Michael D., Shangbin Yang, Senthil Sukumar, et al.. (2023). Impaired Cognitive Function in Immune-TTP Is Better Predicted By Serum Thrombomodulin Than ADAMTS13 Activity: Results of a Longitudinal Multicenter Pilot Study. Blood. 142(Supplement 1). 1258–1258.
8.
Masias, Camila, et al.. (2020). Relapse Prediction Model for Immune-Mediated Thrombotic Thrombocytopenic Purpura. Blood. 136(Supplement 1). 8–9. 2 indexed citations
9.
Masias, Camila, et al.. (2019). Severely Deficient ADAMTS13 Activity Predicts Relapse of Immune-Mediated Thrombotic Thrombocytopenic Purpura in Pregnancy. Blood. 134(Supplement_1). 1098–1098. 3 indexed citations
10.
Chen, Jian, et al.. (2017). Increased complement activation during platelet storage. Transfusion. 57(9). 2182–2188. 20 indexed citations
11.
12.
He, Shun, Min Feng, Mei Liu, et al.. (2014). P21-Activated Kinase 7 Mediates Cisplatin-Resistance of Esophageal Squamous Carcinoma Cells with Aurora-A Overexpression. PLoS ONE. 9(12). e113989–e113989. 20 indexed citations
13.
Zhang, Ju, Xiaomin Lou, Shangbin Yang, et al.. (2011). BAG2 is a target of the c-Myc gene and is involved in cellular senescence via the p21CIP1 pathway. Cancer Letters. 318(1). 34–41. 18 indexed citations
14.
Yang, Shangbin, Lihui Xu, & Haifeng Wu. (2010). Rapid Genotyping of Single Nucleotide Polymorphisms Influencing Warfarin Drug Response by Surface-Enhanced Laser Desorption and Ionization Time-of-Flight (SELDI-TOF) Mass Spectrometry. Journal of Molecular Diagnostics. 12(2). 162–168. 6 indexed citations
15.
Zhang, Wei, Shuang Yan, Guo Zhang, et al.. (2010). β-Catenin/TCF pathway plays a vital role in selenium induced-growth inhibition and apoptosis in esophageal squamous cell carcinoma (ESCC) cells. Cancer Letters. 296(1). 113–122. 21 indexed citations
16.
He, Shun, Shangbin Yang, Mei Liu, et al.. (2010). Aurora kinase A induces miR-17-92 cluster through regulation of E2F1 transcription factor. Cellular and Molecular Life Sciences. 67(12). 2069–2076. 21 indexed citations
17.
Yang, Shangbin, Lihui Xu, & Haifeng Wu. (2010). Rapid Multiplexed Genotyping for Hereditary Thrombophilia by SELDI-TOF Mass Spectrometry. Diagnostic Molecular Pathology. 19(1). 54–61. 2 indexed citations
18.
Yan, Shuang, Cuiqi Zhou, Wei Zhang, et al.. (2008). β-Catenin/TCF pathway upregulates STAT3 expression in human esophageal squamous cell carcinoma. Cancer Letters. 271(1). 85–97. 85 indexed citations
19.
Yang, Shangbin, Lihui Xu, & Haifeng Wu. (2008). Rapid Genotyping of SNPs Influencing Warfarin Drug Response by SELDI-TOF Mass Spectrometry. Blood. 112(11). 4053–4053. 2 indexed citations
20.
Huang, Moli, Yihua Wang, Daochun Sun, et al.. (2006). Identification of genes regulated by Wnt/β-catenin pathway and involved in apoptosis via microarray analysis. BMC Cancer. 6(1). 221–221. 43 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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