Ming-Ming He

2.0k total citations · 1 hit paper
49 papers, 1.3k citations indexed

About

Ming-Ming He is a scholar working on Oncology, Pulmonary and Respiratory Medicine and Cancer Research. According to data from OpenAlex, Ming-Ming He has authored 49 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Oncology, 17 papers in Pulmonary and Respiratory Medicine and 12 papers in Cancer Research. Recurrent topics in Ming-Ming He's work include Colorectal Cancer Treatments and Studies (12 papers), Gastric Cancer Management and Outcomes (11 papers) and Cancer Genomics and Diagnostics (7 papers). Ming-Ming He is often cited by papers focused on Colorectal Cancer Treatments and Studies (12 papers), Gastric Cancer Management and Outcomes (11 papers) and Cancer Genomics and Diagnostics (7 papers). Ming-Ming He collaborates with scholars based in China, United States and Germany. Ming-Ming He's co-authors include Rui‐Hua Xu, Feng Wang, Ying Jin, Qi Zhao, Zexian Liu, Ying-Nan Wang, Hui Luo, Mingyang Song, Zhe Fang and Chao Ren and has published in prestigious journals such as Nature Communications, Journal of Clinical Oncology and PLoS ONE.

In The Last Decade

Ming-Ming He

47 papers receiving 1.3k citations

Hit Papers

Evaluation of POLE and POLD1 Mutations as Biomarkers for ... 2019 2026 2021 2023 2019 50 100 150 200 250

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ming-Ming He China 18 634 381 315 314 220 49 1.3k
Zhongguo Zhou China 21 489 0.8× 335 0.9× 325 1.0× 332 1.1× 353 1.6× 87 1.7k
Yasutaka Sukawa Japan 21 645 1.0× 207 0.5× 269 0.9× 556 1.8× 234 1.1× 52 1.3k
Alexandra Pohl United States 15 539 0.9× 196 0.5× 243 0.8× 332 1.1× 208 0.9× 20 1.1k
Vassiliki L. Tsikitis United States 23 743 1.2× 241 0.6× 255 0.8× 277 0.9× 534 2.4× 92 1.6k
Vladmir Cláudio Cordeiro de Lima Brazil 20 806 1.3× 297 0.8× 478 1.5× 404 1.3× 116 0.5× 90 1.5k
Qifeng Chen China 22 346 0.5× 331 0.9× 323 1.0× 523 1.7× 153 0.7× 83 1.4k
Antonio Zanghì Italy 18 482 0.8× 213 0.6× 274 0.9× 435 1.4× 457 2.1× 88 1.4k
Woosung Lim South Korea 21 434 0.7× 388 1.0× 170 0.5× 351 1.1× 234 1.1× 76 1.2k
Javier de Spain 19 650 1.0× 347 0.9× 272 0.9× 569 1.8× 493 2.2× 38 1.7k
Zhonghua Wang China 22 497 0.8× 351 0.9× 334 1.1× 397 1.3× 136 0.6× 81 1.2k

Countries citing papers authored by Ming-Ming He

Since Specialization
Citations

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

Fields of papers citing papers by Ming-Ming He

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ming-Ming He. 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 Ming-Ming He. The network helps show where Ming-Ming He may publish in the future.

Co-authorship network of co-authors of Ming-Ming He

This figure shows the co-authorship network connecting the top 25 collaborators of Ming-Ming He. A scholar is included among the top collaborators of Ming-Ming He 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 Ming-Ming He. Ming-Ming He 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.
He, Ming-Ming, Jie Wu, Ying Yang, et al.. (2025). The HsfA1a-BAG5b module mediates thermotolerance through activating autophagy in tomato. PLANT PHYSIOLOGY. 199(3). 1 indexed citations
3.
Polychronidis, Georgios, Ming-Ming He, Mathew Vithayathil, et al.. (2024). Risk of colorectal neoplasia after removal of conventional adenomas and serrated polyps: a comprehensive evaluation of risk factors and surveillance use. Gut. 73(10). 1675–1683. 4 indexed citations
4.
Wang, Shixiang, Chen‐Yi Wu, Ming-Ming He, et al.. (2024). Machine learning-based extrachromosomal DNA identification in large-scale cohorts reveals its clinical implications in cancer. Nature Communications. 15(1). 1515–1515. 13 indexed citations
5.
Zhou, Wen, Ming-Ming He, Feng Wang, et al.. (2023). Latent class analysis-derived classification improves the cancer-specific death stratification of molecular subtyping in colorectal cancer. npj Precision Oncology. 7(1). 60–60. 2 indexed citations
6.
He, Heng, Qian Shen, Ming-Ming He, et al.. (2023). In Utero and Childhood/Adolescence Exposure to Tobacco Smoke, Genetic Risk, and Cancer Incidence in Adulthood: A Prospective Cohort Study. Mayo Clinic Proceedings. 98(8). 1164–1176. 2 indexed citations
7.
Zhao, Qianqian, et al.. (2023). Non-linear relationship between sleep duration and blood pressure in children with short stature. Frontiers in Pediatrics. 11. 1302750–1302750. 2 indexed citations
8.
Luo, Xiaojing, Ming-Ming He, Jia Liu, et al.. (2022). LncRNA TMPO-AS1 promotes esophageal squamous cell carcinoma progression by forming biomolecular condensates with FUS and p300 to regulate TMPO transcription. Experimental & Molecular Medicine. 54(6). 834–847. 24 indexed citations
9.
Jiang, Xudong, et al.. (2021). Efficacy of acupuncture for persistent and intractable hiccups. Medicine. 100(8). e24879–e24879. 5 indexed citations
10.
Wang, Feng, Ming-Ming He, Yichen Yao, et al.. (2021). Regorafenib plus toripalimab in patients with metastatic colorectal cancer: a phase Ib/II clinical trial and gut microbiome analysis. Cell Reports Medicine. 2(9). 100383–100383. 108 indexed citations
12.
Fang, Zhe, Ming-Ming He, & Mingyang Song. (2020). Serum lipid profiles and risk of colorectal cancer: a prospective cohort study in the UK Biobank. British Journal of Cancer. 124(3). 663–670. 49 indexed citations
13.
Yang, Lu-Ping, Zixian Wang, Ming-Ming He, et al.. (2019). <p>A real-world evidence of efficacy of palliative gastrectomy plus chemotherapy in metastatic gastric cancer patients</p>. Cancer Management and Research. Volume 11. 3993–4003. 7 indexed citations
14.
Wang, Feng, Ming-Ming He, Zixian Wang, et al.. (2019). Phase I study of high-dose ascorbic acid with mFOLFOX6 or FOLFIRI in patients with metastatic colorectal cancer or gastric cancer. BMC Cancer. 19(1). 460–460. 39 indexed citations
15.
Wei, Xiaoli, Feng‐Hua Wang, Dongsheng Zhang, et al.. (2015). A novel inflammation-based prognostic score in esophageal squamous cell carcinoma: the C-reactive protein/albumin ratio. BMC Cancer. 15(1). 350–350. 140 indexed citations
16.
He, Ming-Ming, Kaihu Yao, Wei Shi, et al.. (2015). Dynamics of serotype 14 Streptococcus pneumoniae population causing acute respiratory infections among children in China (1997–2012). BMC Infectious Diseases. 15(1). 266–266. 17 indexed citations
17.
Wei, Xiaoli, Miao‐Zhen Qiu, Huan‐Xin Lin, et al.. (2014). Patients with Old Age or Proximal Tumors Benefit from Metabolic Syndrome in Early Stage Gastric Cancer. PLoS ONE. 9(3). e89965–e89965. 18 indexed citations
18.
Shi, Wei, Kaihu Yao, Ming-Ming He, Sangjie Yu, & Yonghong Yang. (2014). Population biology of 225 serogroup 6 Streptococcus pneumoniae isolates collected in China. BMC Infectious Diseases. 14(1). 467–467. 6 indexed citations
20.
Ma, Xiang, Kaihu Yao, Shaomei Yu, et al.. (2012). Genotype replacement within serotype 23FStreptococcus pneumoniaein Beijing, China: characterization of serotype 23F. Epidemiology and Infection. 141(8). 1690–1696. 16 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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