Xiaoming Xing

1.9k citations
90 papers · 1.3k · h-index 22

Impact in

  • Oncology top 5%
    • Viral-associated cancers and disorders
    • Peptidase Inhibition and Analysis
    • Protease and Inhibitor Mechanisms

Papers in

Xiaoming Xing

85 papers receiving 1.3k citations

Peers

Xiaoming Xing
Comparison fields: 5 of 116
  • Oncology 483
  • Cancer Research 266
  • Pathology and Forensic Medicine 246
  • Cell Biology 160
  • Nephrology 65
Replace Krzysztof Moroz with:
Krzysztof Moroz United States
Lisa M. Schumaker United States
Toshiyuki Kitano Japan
Gaosong Wu China
Ralph Fritsch Germany
Stephan Macher‐Goeppinger Germany
Toyone Kikumori Japan
Joo Heon Kim South Korea
Harun M. Said Germany
Hannes Neuwirt Austria
Xiaoming Xing relative to Krzysztof Moroz United States Krzysztof Moroz's profile →
Citations per field
00.5×
Krzysztof Moroz · 1×
Citations per year

Countries citing papers authored by Xiaoming Xing

Since Specialization
Citations

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

Fields of papers citing papers by Xiaoming Xing

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Xiaoming Xing, 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 Xing Line = papers co-authored together Xiaoming Xing links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 90 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005111
2 201475
3 201766
4 200466
5 202047
6 202045
7 200643
8 202041
9 201240
10 201038
11 200734
12 201731
13 200930
14 200928
15
Overexpression of catalytic subunit M2 in patients with ovarian cancer.
201228
16 201027
17 200627
18 201024
19 202024
20 202123

About Xiaoming Xing

Xiaoming Xing is a scholar working on Oncology, Molecular Biology, Pulmonary and Respiratory Medicine, Pathology and Forensic Medicine and Cancer Research, having authored 90 papers that have together received 1.3k indexed citations. Recurring topics across this work include Lymphoma Diagnosis and Treatment (11 papers), Genetic factors in colorectal cancer (7 papers), Endoplasmic Reticulum Stress and Disease (6 papers), Viral-associated cancers and disorders (6 papers), Gastrointestinal Tumor Research and Treatment (5 papers), Cancer, Hypoxia, and Metabolism (5 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and Cancer Cells and Metastasis (4 papers). The work is most often cited by research in Oncology (483 citations), Cancer Research (266 citations), Pathology and Forensic Medicine (246 citations), Cell Biology (160 citations) and Nephrology (65 citations). Xiaoming Xing has collaborated with scholars based in China, United States and Sweden. Frequent co-authors include Qiong Huang, Enping Xu, Maode Lai, Andrew L. Feldman, Xiaoping Xia, Yonggang Liu, Bingjian Lü, Bing Luo, Lili Wang and Dongliang Lin. Their work appears in journals such as BMC Cancer, Frontiers in Oncology, Oral Surgery Oral Medicine Oral Pathology and Oral Radiology, Cancer Cell International and PeerJ.

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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