Xiaoming Cheng

3.9k citations
67 papers · 1.9k · 1 hit paper · h-index 21

Impact in

Papers in

Xiaoming Cheng

63 papers receiving 1.9k citations

Xiaoming Cheng's Hit Papers

Profiling serum cytokines in COVID-19 patients reveals IL-6 and IL-10 are disease severity predictors 2020 · 830 citations
8300+2+4Years since publication250500750

Peers

Xiaoming Cheng
Comparison fields: 5 of 122
  • Infectious Diseases 748
  • Hepatology 298
  • Neurology 403
  • Epidemiology 528
  • Immunology 241
Replace Jiong Yu with:
Jiong Yu China
Yingan Jiang China
Prasenjit Das India
Jordan E. Axelrad United States
Carmen Guerrero Spain
Zhongji Meng China
Der‐Yuan Chen Taiwan
Sebastian Weis Germany
Yueyong Zhu China
Yujun Tang China
Xiaoming Cheng relative to Jiong Yu China Jiong Yu's profile →
Citations per field
00.5×1.6×
Jiong Yu · 1×
Citations per year

Countries citing papers authored by Xiaoming Cheng

Since Specialization
Citations

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

Fields of papers citing papers by Xiaoming Cheng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Xiaoming Cheng, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Xiaoming Cheng Line = papers co-authored together Xiaoming Cheng links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 67 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Profiling serum cytokines in COVID-19 patients reveals IL-6 and IL-10 are disease severity predictors
Hit paper breakdown →
2020830
2 2017123
3 2016103
4 201848
5 202046
6 202046
7 201845
8 202140
9 202236
10 201935
11 202034
12 202334
13 201432
14
Role of succinylation modification in thyroid cancer and breast cancer.
202129
15
Identification of HLA-A*0201-restricted cytotoxic T lymphocyte epitope from TRAG-3 antigen.
200328
16 201826
17 201726
18 202324
19 201724
20 202321

About Xiaoming Cheng

Xiaoming Cheng is a scholar working on Epidemiology, Molecular Biology, Hepatology, Cancer Research and Oncology, having authored 67 papers that have together received 1.9k indexed citations. Recurring topics across this work include Hepatitis B Virus Studies (25 papers), Hepatitis C virus research (12 papers), Breast Cancer Treatment Studies (6 papers), Liver Disease Diagnosis and Treatment (6 papers), Cancer, Hypoxia, and Metabolism (6 papers), Hepatitis Viruses Studies and Epidemiology (5 papers), Thyroid Cancer Diagnosis and Treatment (5 papers) and Immunotherapy and Immune Responses (4 papers). The work is most often cited by research in Infectious Diseases (748 citations), Hepatology (298 citations), Neurology (403 citations), Epidemiology (528 citations) and Immunology (241 citations). Xiaoming Cheng has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Yuchen Xia, Chengliang Zhu, Huan Han, Yingan Jiang, Li Zhao, Guosheng Gao, Fang Liu, Qingfeng Ma, Pingan Zhang and Rui Liu. Their work appears in journals such as Journal of Virology, Antiviral Research, PLoS Pathogens, Cancer Gene Therapy and Hepatology.

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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