Xiaoya Ma

1.2k citations
27 papers · 810 indexed · h-index 14

Impact in

  • Hematology top 10%
    • Iron Metabolism and Disorders
    • Cancer-related molecular mechanisms research
    • Cancer, Hypoxia, and Metabolism

Papers in

Xiaoya Ma

26 papers receiving 802 citations

Peers

Xiaoya Ma
Comparison fields: 5 of 99
  • Hematology 133
  • Cancer Research 161
  • Nutrition and Dietetics 94
  • Immunology 112
  • Molecular Biology 343
Replace Tsuyako Saito with:
Tsuyako Saito Japan
Hilde Schjerven United States
Chiara Sartor Italy
Adam T. Boutin United States
Akira Moh United States
Jia Tong China
Mairi McGrath Germany
Leticia Rocha‐Zavaleta Mexico
Zhu Shen China
Charlene F. Barroga United States
Xiaoya Ma relative to Tsuyako Saito Japan Tsuyako Saito's profile →
Citations per field
00.5×10×20×32×
Tsuyako Saito · 1×
Citations per year

Countries citing papers authored by Xiaoya Ma

Since Specialization
Citations

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

Fields of papers citing papers by Xiaoya Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20251
2 20240
3 20244
4 20238
5 202317
6 202310
7 20235
8 20224
9 202228
10 202216
11 202110
12 20207
13 201975
14 2019213
15 201956
16 2018127
17 201731
18 201744
19 201450
20 201318

About Xiaoya Ma

Xiaoya Ma is a scholar working on Cancer Research, Agronomy and Crop Science, Biochemistry, Hematology and Immunology, having authored 27 papers that have together received 810 indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (3 papers), Gut microbiota and health (3 papers), Cancer, Hypoxia, and Metabolism (3 papers), Genetic and phenotypic traits in livestock (3 papers), Iron Metabolism and Disorders (3 papers), Adipose Tissue and Metabolism (3 papers), Cardiovascular, Neuropeptides, and Oxidative Stress Research (2 papers) and Genetic Mapping and Diversity in Plants and Animals (2 papers). The work is most often cited by research in Hematology (133 citations), Cancer Research (161 citations), Nutrition and Dietetics (94 citations), Immunology (112 citations) and Molecular Biology (343 citations). Xiaoya Ma has collaborated with scholars based in China, United States and Egypt. Frequent co-authors include Yatrik M. Shah, Gabriel Núñez, Naohiro Inohara, Nupur K. Das, Andrew J. Schwartz, Sadeesh K. Ramakrishnan, Samantha N. Devenport, Xiang Xue, Daniel Triner and Amanda Sankar. Their work appears in journals such as International Journal of Molecular Sciences, Journal of Biological Chemistry, mSystems, iScience and Veterinary Research Communications.

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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