Xun Ma

449 total citations
31 papers, 269 citations indexed

About

Xun Ma is a scholar working on Molecular Biology, Rheumatology and Immunology. According to data from OpenAlex, Xun Ma has authored 31 papers receiving a total of 269 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 8 papers in Rheumatology and 6 papers in Immunology. Recurrent topics in Xun Ma's work include Osteoarthritis Treatment and Mechanisms (7 papers), Monoclonal and Polyclonal Antibodies Research (5 papers) and Amyloidosis: Diagnosis, Treatment, Outcomes (5 papers). Xun Ma is often cited by papers focused on Osteoarthritis Treatment and Mechanisms (7 papers), Monoclonal and Polyclonal Antibodies Research (5 papers) and Amyloidosis: Diagnosis, Treatment, Outcomes (5 papers). Xun Ma collaborates with scholars based in United States, China and Italy. Xun Ma's co-authors include Xueyong Liu, Chakra P. Chaulagain, Raymond L. Comenzo, Ping Zhou, Zhan Zhang, Bo Song, Xinjing Liu, Lakshmanan K. Iyer, Yuming Xu and Guangming Gong and has published in prestigious journals such as Journal of Clinical Oncology, Blood and PLoS ONE.

In The Last Decade

Xun Ma

26 papers receiving 265 citations

Peers

Xun Ma
Comparison fields: 5 of 46
  • Molecular Biology 124
  • Oncology 45
  • Neurology 43
  • Immunology 36
  • Rheumatology 34
Replace Sonia Gavasso with:
Sonia Gavasso Norway
Sandra Gallagher United States
Yujie Cui China
Yaru Su China
Gordon Byrnes United States
Amy Andreucci United States
Hongcheng Luo China
Romain Guiho France
Edoardo Pedrini Italy
Javier del Pino Montes Spain
Sonia Gavasso Norway View profile →
Citations per field, relative to Xun Ma
Xun Ma · 1×
Citations per year, relative to Xun Ma
Xun Ma · 1×

Countries citing papers authored by Xun Ma

Since Specialization
Citations

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

Fields of papers citing papers by Xun Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xun Ma

This figure shows the co-authorship network connecting the top 25 collaborators of Xun Ma. A scholar is included among the top collaborators of Xun 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 Xun Ma. Xun 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
# Work Indexed citations
1 1
2 0
3 0
4 2
5 3
6 2
7 0
8 11
9 4
10 9
11 5
12 2
13 21
14 6
15 38
16 52
17 2
18
Muc16 carboxyl portion expression alternates PI3K/Akt and EGFR/HER2/ERK signal pathways in human ovarian cells
1
19
MUC16 gene up-regulates gene transcripts associated with cisplatin resistance in human ovarian cancer cells
1
20 5

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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