Dexuan Ma

713 citations
21 papers · 526 · h-index 13

Impact in

Papers in

Dexuan Ma

20 papers receiving 521 citations

Peers

Dexuan Ma
Comparison fields: 5 of 77
  • Developmental Neuroscience 41
  • Cancer Research 101
  • Behavioral Neuroscience 22
  • Cellular and Molecular Neuroscience 99
  • Nutrition and Dietetics 83
Replace Yoshiteru Kagawa with:
Yoshiteru Kagawa Japan
М. В. Глазова Russia
Pelin Cengiz United States
Ning Bai China
Kalpana Shrivastava Spain
Yan Zhan China
Sookhee Bang United States
Nicolas Pelisch Japan
Crissey L. Pascale United States
Ravinder Pannu United States
Dexuan Ma relative to Yoshiteru Kagawa Japan Yoshiteru Kagawa's profile →
Citations per field
00.5×1.5×
Yoshiteru Kagawa · 1×
Citations per year

Countries citing papers authored by Dexuan Ma

Since Specialization
Citations

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

Fields of papers citing papers by Dexuan Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200792
2 200776
3 201064
4 201763
5 201644
6 201533
7 200924
8 200823
9 201619
10 201019
11 201516
12 202312
13 201712
14 201510
15 20119
16 20174
17 20182
18 20172
19 20201
20 20181

About Dexuan Ma

Dexuan Ma is a scholar working on Molecular Biology, Cancer Research, Cellular and Molecular Neuroscience, Neurology and Cell Biology, having authored 21 papers that have together received 526 indexed citations. Recurring topics across this work include Cancer, Hypoxia, and Metabolism (9 papers), Epigenetics and DNA Methylation (4 papers), Neuroblastoma Research and Treatments (3 papers), Neuropeptides and Animal Physiology (3 papers), Traumatic Brain Injury Research (2 papers), Hippo pathway signaling and YAP/TAZ (2 papers), Fibroblast Growth Factor Research (2 papers) and Neuroscience and Neuropharmacology Research (2 papers). The work is most often cited by research in Developmental Neuroscience (41 citations), Cancer Research (101 citations), Behavioral Neuroscience (22 citations), Cellular and Molecular Neuroscience (99 citations) and Nutrition and Dietetics (83 citations). Dexuan Ma has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Tetsumori Yamashima, Liangfu Zhou, Yoshimi Mori, Li Lu, Anton B. Tonchev, Jingyun Yang, Ying Mao, Susumu Kotani, Bangbao Tao and Masa‐aki Nakaya. Their work appears in journals such as Medicine, Hippocampus, Journal of Visualized Experiments, Molecular Carcinogenesis and Scientific Reports.

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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