Ma-Yan Huang

2.0k total citations · 1 hit paper
9 papers, 1.6k citations indexed

About

Ma-Yan Huang is a scholar working on Molecular Biology, Cancer Research and Cell Biology. According to data from OpenAlex, Ma-Yan Huang has authored 9 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 4 papers in Cancer Research and 2 papers in Cell Biology. Recurrent topics in Ma-Yan Huang's work include Cancer-related molecular mechanisms research (3 papers), MicroRNA in disease regulation (3 papers) and Circular RNAs in diseases (2 papers). Ma-Yan Huang is often cited by papers focused on Cancer-related molecular mechanisms research (3 papers), MicroRNA in disease regulation (3 papers) and Circular RNAs in diseases (2 papers). Ma-Yan Huang collaborates with scholars based in China and Sweden. Ma-Yan Huang's co-authors include Yi-Xin Zeng, Jian‐Yong Shao, Qiong Shao, Qiu-Liang Wu, Li‐Xu Yan, Ling Deng, Jing-Hui Hou, Yuhong Li, Dan Xie and Mu‐Sheng Zeng and has published in prestigious journals such as Cancer Research, RNA and Experimental Biology and Medicine.

In The Last Decade

Ma-Yan Huang

9 papers receiving 1.6k citations

Hit Papers

MicroRNA miR-21 overexpression in human breast cancer is ... 2008 2026 2014 2020 2008 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ma-Yan Huang China 9 1.3k 1.1k 225 96 71 9 1.6k
Bi-Jun Huang China 20 900 0.7× 597 0.5× 283 1.3× 163 1.7× 99 1.4× 29 1.2k
Chi Lam Au Yeung United States 7 913 0.7× 758 0.7× 214 1.0× 135 1.4× 55 0.8× 15 1.2k
Ryunosuke Kogo Japan 14 1.6k 1.3× 1.7k 1.5× 242 1.1× 62 0.6× 95 1.3× 38 2.1k
Emine Bayraktar United States 16 1.2k 0.9× 802 0.7× 146 0.6× 166 1.7× 94 1.3× 41 1.4k
Qiong Shao China 17 1.3k 1.0× 1.1k 1.0× 446 2.0× 125 1.3× 219 3.1× 41 1.8k
Nilva K. Cervigne Brazil 16 730 0.6× 560 0.5× 211 0.9× 57 0.6× 117 1.6× 26 1.1k
Natalia Ramírez Spain 14 1.3k 1.0× 1.3k 1.1× 230 1.0× 158 1.6× 62 0.9× 32 1.7k
Guixi Zheng China 24 1.2k 0.9× 1.2k 1.1× 254 1.1× 110 1.1× 168 2.4× 55 1.7k
Youtao Xu China 21 1.6k 1.2× 1.4k 1.3× 249 1.1× 74 0.8× 294 4.1× 43 2.0k
Bruno Pereira Portugal 13 773 0.6× 376 0.3× 153 0.7× 66 0.7× 68 1.0× 20 1.0k

Countries citing papers authored by Ma-Yan Huang

Since Specialization
Citations

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

Fields of papers citing papers by Ma-Yan Huang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ma-Yan Huang. 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 Ma-Yan Huang. The network helps show where Ma-Yan Huang may publish in the future.

Co-authorship network of co-authors of Ma-Yan Huang

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

All Works

9 of 9 papers shown
1.
Wang, Yun, Ma-Yan Huang, Qiong Shao, et al.. (2017). The Immunoscore system predicts prognosis after liver metastasectomy in colorectal cancer liver metastases. Cancer Immunology Immunotherapy. 67(3). 435–444. 60 indexed citations
2.
Wang, Yun, Yang Zhao, Ma-Yan Huang, et al.. (2015). Effect of Raf kinase inhibitor protein expression on malignant biological behavior and progression of colorectal cancer. Oncology Reports. 34(4). 2106–2114. 12 indexed citations
3.
Wang, Haiyun, Yang Yang Li, Sha Fu, et al.. (2014). MicroRNA-30a promotes invasiveness and metastasis in vitro and in vivo through epithelial–mesenchymal transition and results in poor survival of nasopharyngeal carcinoma patients. Experimental Biology and Medicine. 239(7). 891–898. 28 indexed citations
4.
Zhang, Jiaxing, Zhu‐Ting Tong, Jie-Wei Chen, et al.. (2012). Overexpression of the secretory small GTPase Rab27B in human breast cancer correlates closely with lymph node metastasis and predicts poor prognosis. Journal of Translational Medicine. 10(1). 242–242. 41 indexed citations
5.
Zhang, Jiaxing, Qiong Shao, Zhu‐Ting Tong, et al.. (2012). Elevated DLL4 expression is correlated with VEGF and predicts poor prognosis of nasopharyngeal carcinoma. Medical Oncology. 30(1). 390–390. 38 indexed citations
6.
Zhang, Yan, Li‐Xu Yan, Qi-Nian Wu, et al.. (2011). miR-125b Is Methylated and Functions as a Tumor Suppressor by Regulating the ETS1 Proto-oncogene in Human Invasive Breast Cancer. Cancer Research. 71(10). 3552–3562. 237 indexed citations
7.
Li, Yuhong, Qiong Shao, Ma-Yan Huang, et al.. (2008). Elevated expressions of survivin and VEGF protein are strong independent predictors of survival in advanced nasopharyngeal carcinoma. Journal of Translational Medicine. 6(1). 1–1. 159 indexed citations
8.
Yan, Li‐Xu, Qiong Shao, Ma-Yan Huang, et al.. (2008). MicroRNA miR-21 overexpression in human breast cancer is associated with advanced clinical stage, lymph node metastasis and patient poor prognosis. RNA. 14(11). 2348–2360. 956 indexed citations breakdown →
9.
Cao, Yun, Xiaoping Miao, Ma-Yan Huang, et al.. (2006). Polymorphisms of XRCC1 genes and risk of nasopharyngeal carcinoma in the Cantonese population. BMC Cancer. 6(1). 167–167. 52 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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