Yihong Wang

8.2k total citations · 2 hit papers
140 papers, 4.9k citations indexed

About

Yihong Wang is a scholar working on Pathology and Forensic Medicine, Oncology and Cancer Research. According to data from OpenAlex, Yihong Wang has authored 140 papers receiving a total of 4.9k indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Pathology and Forensic Medicine, 40 papers in Oncology and 36 papers in Cancer Research. Recurrent topics in Yihong Wang's work include Breast Lesions and Carcinomas (32 papers), Breast Cancer Treatment Studies (22 papers) and Cancer and Skin Lesions (17 papers). Yihong Wang is often cited by papers focused on Breast Lesions and Carcinomas (32 papers), Breast Cancer Treatment Studies (22 papers) and Cancer and Skin Lesions (17 papers). Yihong Wang collaborates with scholars based in United States, China and Canada. Yihong Wang's co-authors include Leon V. Kochian, David F. Garvin, Chen Dong, Seon Hee Chang, Towia A. Libermann, Luiz F. Zerbini, Roza Nurieva, Natalia Martín‐Orozco, Yong-Jun Liu and Je‐Yoel Cho and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

In The Last Decade

Yihong Wang

133 papers receiving 4.8k citations

Hit Papers

Regulation of inflammatory responses by IL-17F 2007 2026 2013 2019 2008 2007 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yihong Wang United States 31 1.5k 1.2k 1.2k 770 606 140 4.9k
Pin Wu China 42 1.1k 0.7× 1.7k 1.4× 1.4k 1.1× 1.5k 1.9× 149 0.2× 104 4.6k
Mei Huang China 41 808 0.5× 3.5k 2.9× 889 0.7× 652 0.8× 439 0.7× 123 6.1k
Cécile Guichard France 22 574 0.4× 1.6k 1.3× 424 0.3× 311 0.4× 352 0.6× 35 3.5k
Hideo Kaneko Japan 31 722 0.5× 1.3k 1.1× 493 0.4× 381 0.5× 346 0.6× 242 3.5k
Frank Petersen Germany 41 1.5k 0.9× 2.1k 1.7× 199 0.2× 1.3k 1.6× 301 0.5× 143 5.6k
Rebecca Lamb United Kingdom 39 841 0.5× 2.9k 2.4× 1.3k 1.1× 796 1.0× 219 0.4× 66 4.9k
Cédric Simillion Switzerland 29 645 0.4× 2.0k 1.6× 907 0.7× 327 0.4× 393 0.6× 59 3.6k
Ulla Hansen United States 40 601 0.4× 3.1k 2.6× 330 0.3× 899 1.2× 1.2k 2.0× 104 5.4k
Fujio Otsuka Japan 30 1.4k 0.9× 2.0k 1.6× 209 0.2× 825 1.1× 386 0.6× 178 5.4k
Da Fu China 40 567 0.4× 3.1k 2.6× 433 0.4× 922 1.2× 314 0.5× 165 5.0k

Countries citing papers authored by Yihong Wang

Since Specialization
Citations

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

Fields of papers citing papers by Yihong Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yihong Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Yihong Wang. A scholar is included among the top collaborators of Yihong 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 Yihong Wang. Yihong 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
2.
Dong, Huijun, et al.. (2025). A LASSO-based integrative model of serum biomarkers and gene polymorphisms for predicting poor sepsis prognosis. Biomarkers in Medicine. 19(20). 1009–1018.
3.
Shen, Qi, et al.. (2025). Association Analysis and Identification of Candidate Genes for Sorghum Coleoptile Color. Agronomy. 15(3). 688–688. 1 indexed citations
4.
Fineberg, Susan, et al.. (2023). Pathological response in mucinous carcinoma of breast after neoadjuvant therapy - a multi-institutional study. Human Pathology. 142. 15–19. 3 indexed citations
6.
Pavlick, Dean C., Yihong Wang, Benedito A. Carneiro, et al.. (2023). Comprehensive Genomic Profiling of NF2-Mutated Kidney Tumors Reveals Potential Targets for Therapy. The Oncologist. 28(7). e508–e519. 9 indexed citations
7.
Figueroa, Jonine D., Gretchen L. Gierach, Máire A. Duggan, et al.. (2021). Risk factors for breast cancer development by tumor characteristics among women with benign breast disease. Breast Cancer Research. 23(1). 34–34. 21 indexed citations
8.
Wang, Yihong, Kamaljeet Singh, Don S. Dizon, et al.. (2021). Immunohistochemical HER2 score correlates with response to neoadjuvant chemotherapy in HER2-positive primary breast cancer. Breast Cancer Research and Treatment. 186(3). 667–676. 8 indexed citations
9.
Rohan, Thomas E., Tao Wang, Sheila Weinmann, et al.. (2019). A miRNA Expression Signature in Breast Tumor Tissue Is Associated with Risk of Distant Metastasis. Cancer Research. 79(7). 1705–1713. 13 indexed citations
10.
Huang, Aihua, Zhifeng Wu, Yihong Wang, et al.. (2019). Infiltrating regulatory T cells promote invasiveness of liver cancer cells via inducing epithelial-mesenchymal transition. Translational Cancer Research. 8(6). 2405–2415. 2 indexed citations
11.
Ma, Yutao, Tao Xu, Xiaolei Huang, et al.. (2019). Computer-Aided Diagnosis of Label-Free 3-D Optical Coherence Microscopy Images of Human Cervical Tissue. IEEE Transactions on Biomedical Engineering. 66(9). 2447–2456. 32 indexed citations
12.
Ward, Robert C., et al.. (2019). Pilomatricoma of the male breast. The Breast Journal. 25(5). 1012–1013. 2 indexed citations
13.
Suyama, Kimita, Jiahong Yao, Outhiriaradjou Benard, et al.. (2017). An Akt3 Splice Variant Lacking the Serine 472 Phosphorylation Site Promotes Apoptosis and Suppresses Mammary Tumorigenesis. Cancer Research. 78(1). 103–114. 14 indexed citations
15.
Brodsky, Alexander S., Dongfang Yang, Christoph Schorl, et al.. (2016). Identification of stromal ColXα1 and tumor-infiltrating lymphocytes as putative predictive markers of neoadjuvant therapy in estrogen receptor-positive/HER2-positive breast cancer. BMC Cancer. 16(1). 274–274. 38 indexed citations
16.
Voo, Kui Shin, Yui‐Hsi Wang, Fabio R. Santori, et al.. (2009). Identification of IL-17-producing FOXP3+ regulatory T cells in humans (89.1). The Journal of Immunology. 182(Supplement_1). 89.1–89.1. 28 indexed citations
17.
Yang, Xuexian O., Seon Hee Chang, Heon Park, et al.. (2008). Regulation of inflammatory responses by IL-17F. The Journal of Experimental Medicine. 205(5). 1063–1075. 625 indexed citations breakdown →
18.
Zerbini, Luiz F., Akos Czibere, Yihong Wang, et al.. (2006). A Novel Pathway Involving Melanoma Differentiation Associated Gene-7/Interleukin-24 Mediates Nonsteroidal Anti-inflammatory Drug–Induced Apoptosis and Growth Arrest of Cancer Cells. Cancer Research. 66(24). 11922–11931. 48 indexed citations
19.
Zerbini, Luiz F., Yihong Wang, Je‐Yoel Cho, & Towia A. Libermann. (2003). Constitutive activation of nuclear factor kappaB p50/p65 and Fra-1 and JunD is essential for deregulated interleukin 6 expression in prostate cancer.. PubMed. 63(9). 2206–15. 145 indexed citations
20.
Wang, Yihong, Whaseon Lee‐Kwon, Jennifer L. Martindale, et al.. (1999). Modulation of CCAAT/Enhancer-Binding Protein-α Gene Expression by Metabolic Signals in Rodent Adipocytes. Endocrinology. 140(7). 2938–2947. 7 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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