Xiaofeng Wan

542 citations
33 papers · 313 · h-index 12

Impact in

Papers in

    • PI3K/AKT/mTOR signaling in cancer 5
    • Wildlife Ecology and Conservation 5
    • Animal Ecology and Behavior Studies 5

Xiaofeng Wan

31 papers receiving 310 citations

Peers

Xiaofeng Wan
Comparison fields: 5 of 77
  • Ecological Modeling 18
  • Reproductive Medicine 35
  • Ecology 73
  • Cancer Research 43
  • Genetics 58
Replace Ming Tu with:
Ming Tu China
Jeremy R. Egbert United States
Christian Schauer Austria
Shelley Valle United States
Michał J. Dąbrowski Poland
Akira Oike Japan
Allison E. Drew United States
Stephanie J. Smith Australia
Silvia Gravina United States
Hu Nie China
Xiaofeng Wan relative to Ming Tu China Ming Tu's profile →
Citations per field
00.5×4.3×
Ming Tu · 1×
Citations per year

Countries citing papers authored by Xiaofeng Wan

Since Specialization
Citations

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

Fields of papers citing papers by Xiaofeng Wan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200643
2 202423
3 201722
4 202118
5 201018
6 201917
7 199616
8 200916
9 201614
10 202112
11 202111
12 201611
13 202011
14 202011
15 201110
16 20238
17 20208
18 20217
19 20087
20 20196

About Xiaofeng Wan

Xiaofeng Wan is a scholar working on Molecular Biology, Ecology, Immunology, Reproductive Medicine and Radiology, Nuclear Medicine and Imaging, having authored 33 papers that have together received 313 indexed citations. Recurring topics across this work include Wildlife Ecology and Conservation (5 papers), Animal Ecology and Behavior Studies (5 papers), PI3K/AKT/mTOR signaling in cancer (5 papers), Sperm and Testicular Function (5 papers), Tuberous Sclerosis Complex Research (3 papers), Ecology and Vegetation Dynamics Studies (3 papers), Ferroptosis and cancer prognosis (3 papers) and Radiomics and Machine Learning in Medical Imaging (3 papers). The work is most often cited by research in Ecological Modeling (18 citations), Reproductive Medicine (35 citations), Ecology (73 citations), Cancer Research (43 citations) and Genetics (58 citations). Xiaofeng Wan has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Wenqin Zhong, Wei Liu, Guiming Wang, Xiaojun Zha, Yonglian Zhang, Yuchuan Zhou, Qianqian Yin, Qiang Liu, Jia Shen and Meng Zhou. Their work appears in journals such as Journal of Arid Environments, Endocrinology, Cell Death and Disease, Acta Biochimica et Biophysica Sinica and Molecular Therapy — Oncolytics.

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.

Explore authors with similar magnitude of impact