Ben Ma

2.1k total citations
65 papers, 1.5k citations indexed

About

Ben Ma is a scholar working on Endocrinology, Diabetes and Metabolism, Molecular Biology and Surgery. According to data from OpenAlex, Ben Ma has authored 65 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Endocrinology, Diabetes and Metabolism, 20 papers in Molecular Biology and 17 papers in Surgery. Recurrent topics in Ben Ma's work include Thyroid Cancer Diagnosis and Treatment (31 papers), Thyroid and Parathyroid Surgery (10 papers) and Ferroptosis and cancer prognosis (9 papers). Ben Ma is often cited by papers focused on Thyroid Cancer Diagnosis and Treatment (31 papers), Thyroid and Parathyroid Surgery (10 papers) and Ferroptosis and cancer prognosis (9 papers). Ben Ma collaborates with scholars based in China, United States and Japan. Ben Ma's co-authors include Shuwen Yang, Tian Liao, Qinghai Ji, Qinghai Ji, Yu Wang, Zhong‐Wu Lu, Ning Qu, Wenjun Wei, Yulong Wang and Duo Wen and has published in prestigious journals such as Advanced Materials, Nature Communications and Journal of Clinical Oncology.

In The Last Decade

Ben Ma

64 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ben Ma China 22 514 476 338 304 280 65 1.5k
Ângela M. Costa Portugal 14 277 0.5× 433 0.9× 228 0.7× 347 1.1× 134 0.5× 26 1.0k
Aditi Mukherjee United States 14 192 0.4× 1.3k 2.7× 154 0.5× 460 1.5× 317 1.1× 23 1.8k
Maria Cristina Curia Italy 22 165 0.3× 691 1.5× 183 0.5× 793 2.6× 224 0.8× 61 1.7k
Jing Zhou China 23 160 0.3× 964 2.0× 239 0.7× 216 0.7× 450 1.6× 94 1.6k
Ji Lei China 23 194 0.4× 741 1.6× 477 1.4× 262 0.9× 569 2.0× 53 2.4k
Bin Lang China 21 207 0.4× 577 1.2× 381 1.1× 103 0.3× 382 1.4× 48 1.1k
Laura Ravanti Finland 13 129 0.3× 469 1.0× 152 0.4× 298 1.0× 562 2.0× 16 1.5k
Emma Marshman United Kingdom 11 138 0.3× 506 1.1× 136 0.4× 353 1.2× 126 0.5× 14 963
Andreas R. Günthert Germany 24 106 0.2× 346 0.7× 416 1.2× 239 0.8× 101 0.4× 52 1.4k
Francesca Collina Italy 22 73 0.1× 680 1.4× 85 0.3× 581 1.9× 428 1.5× 49 1.3k

Countries citing papers authored by Ben Ma

Since Specialization
Citations

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

Fields of papers citing papers by Ben Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ben Ma

This figure shows the co-authorship network connecting the top 25 collaborators of Ben Ma. A scholar is included among the top collaborators of Ben Ma 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 Ben Ma. Ben Ma 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.
Li, Qiang, Weituo Zhang, Tian Liao, et al.. (2024). An Artificial Intelligence–Driven Preoperative Radiomic Subtype for Predicting the Prognosis and Treatment Response of Patients with Papillary Thyroid Carcinoma. Clinical Cancer Research. 31(1). 139–150. 2 indexed citations
2.
Qu, Ning, Di Chen, Ben Ma, et al.. (2024). Integrated proteogenomic and metabolomic characterization of papillary thyroid cancer with different recurrence risks. Nature Communications. 15(1). 3175–3175. 18 indexed citations
3.
Ma, Ben, Yi Luo, Weibo Xu, et al.. (2023). LINC00886 Negatively Regulates Malignancy in Anaplastic Thyroid Cancer. Endocrinology. 164(4). 6 indexed citations
4.
Ma, Ben, Yi Luo, Yichen Yang, et al.. (2022). Targeting Tumor Hypoxia Inhibits Aggressive Phenotype of Dedifferentiated Thyroid Cancer. The Journal of Clinical Endocrinology & Metabolism. 108(2). 368–384. 9 indexed citations
5.
Ma, Ben, et al.. (2022). Bronchogenic cysts with infection in the chest wall skin of a 64-year-old asymptomatic patient: A case report. World Journal of Clinical Cases. 10(23). 8392–8399. 1 indexed citations
6.
Xu, Weibo, Cuiwei Li, Ben Ma, et al.. (2021). Identification of Key Functional Gene Signatures Indicative of Dedifferentiation in Papillary Thyroid Cancer. Frontiers in Oncology. 11. 641851–641851. 5 indexed citations
7.
8.
Hu, Jia‐Qian, Duo Wen, Ben Ma, et al.. (2020). IL-2 enhanced MHC class I expression in papillary thyroid cancer with Hashimoto's thyroiditis overcomes immune escape in vitro. Journal of Cancer. 11(14). 4250–4260. 17 indexed citations
9.
Ma, Ben, Hongyi Jiang, Duo Wen, et al.. (2019). Transcriptome Analyses Identify a Metabolic Gene Signature Indicative of Dedifferentiation of Papillary Thyroid Cancer. The Journal of Clinical Endocrinology & Metabolism. 104(9). 3713–3725. 32 indexed citations
10.
Patel, Ravi B., Mingzhou Ye, Peter M. Carlson, et al.. (2019). Development of an In Situ Cancer Vaccine via Combinational Radiation and Bacterial‐Membrane‐Coated Nanoparticles. Advanced Materials. 31(43). e1902626–e1902626. 189 indexed citations
11.
12.
Qu, Ning, Rong‐Liang Shi, Tian Liao, et al.. (2019). Germline Missense Mutation of Deleted in Malignant Brain Tumor 1 (<b><i>DMBT1</i></b>) in Familial Mediastinal Neuroendocrine Cancer and in vitro Effects in Thyroid Cancer Cells. Neuroendocrinology. 110(7-8). 714–720. 1 indexed citations
13.
Han, Litao, Jia‐Qian Hu, Ben Ma, et al.. (2019). IL-17A increases MHC class I expression and promotes T cell activation in papillary thyroid cancer patients with coexistent Hashimoto’s thyroiditis. Diagnostic Pathology. 14(1). 52–52. 17 indexed citations
14.
Ma, Ben, Weibo Xu, Wenjun Wei, et al.. (2018). Clinicopathological and Survival Outcomes of Well-Differentiated Thyroid Carcinoma Undergoing Dedifferentiation: A Retrospective Study from FUSCC. International Journal of Endocrinology. 2018. 1–11. 17 indexed citations
15.
Liao, Tian, Wen‐Jun Wei, Duo Wen, et al.. (2018). Verteporfin inhibits papillary thyroid cancer cells proliferation and cell cycle through ERK1/2 signaling pathway. Journal of Cancer. 9(8). 1329–1336. 12 indexed citations
16.
Yang, Shuwen, Li Zhou, Zhong‐Wu Lu, et al.. (2017). Systematic review with meta-analysis of intraoperative neuromonitoring during thyroidectomy. International Journal of Surgery. 39. 104–113. 105 indexed citations
17.
Ma, Ben, Tian Liao, Duo Wen, et al.. (2016). Long intergenic non-coding RNA 271 is predictive of a poorer prognosis of papillary thyroid cancer. Scientific Reports. 6(1). 36973–36973. 40 indexed citations
18.
Ma, Ben, Yu Wang, Shuwen Yang, & Qinghai Ji. (2016). Predictive factors for central lymph node metastasis in patients with cN0 papillary thyroid carcinoma: A systematic review and meta-analysis. International Journal of Surgery. 28. 153–161. 71 indexed citations
19.
Shi, Rong-Liang, Ning Qu, Tian Liao, et al.. (2016). Relationship of body mass index with BRAF V600E mutation in papillary thyroid cancer. Tumor Biology. 37(6). 8383–8390. 10 indexed citations
20.
Liang, Lizhong, Ben Ma, Yujie Liang, et al.. (2012). High expression of the autophagy gene Beclin‐1 is associated with favorable prognosis for salivary gland adenoid cystic carcinoma. Journal of Oral Pathology and Medicine. 41(8). 621–629. 24 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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