Xiaolan Fan

2.3k citations
77 papers · 1.7k · h-index 23

Impact in

  • Aging top 1%
    • Genetics, Aging, and Longevity in Model Organisms
    • Cancer-related molecular mechanisms research
    • MicroRNA in disease regulation

Papers in

    • Genomics and Phylogenetic Studies 7
    • Gut microbiota and health 6
    • RNA Research and Splicing 5
    • Genetics, Aging, and Longevity in Model Organisms 16

Xiaolan Fan

73 papers receiving 1.6k citations

Peers

Xiaolan Fan
Comparison fields: 5 of 116
  • Aging 170
  • Cancer Research 242
  • Molecular Biology 867
  • Biological Psychiatry 29
  • Cellular and Molecular Neuroscience 209
Replace Uma Gaur with:
Uma Gaur China
Haiyang Chen China
Deying Yang China
Kyung‐Ho Lee South Korea
Susana Castro‐Obregón Mexico
Mitsuaki Fujimoto Japan
Kyu‐Sun Lee South Korea
Yang Cao China
Qing Zhu China
Joshua Wollam United States
Xiaolan Fan relative to Uma Gaur China Uma Gaur's profile →
Citations per field
00.5×
Uma Gaur · 1×
Citations per year

Countries citing papers authored by Xiaolan Fan

Since Specialization
Citations

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

Fields of papers citing papers by Xiaolan Fan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 77 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019126
2 201994
3 202093
4 202290
5 202185
6 201565
7 200962
8 202262
9 202061
10 201660
11 200959
12 202055
13 202053
14 201952
15 201533
16 201633
17 200831
18 200731
19 200931
20 202028

About Xiaolan Fan

Xiaolan Fan is a scholar working on Molecular Biology, Aging, Immunology, Cancer Research and Cellular and Molecular Neuroscience, having authored 77 papers that have together received 1.7k indexed citations. Recurring topics across this work include Genetics, Aging, and Longevity in Model Organisms (16 papers), Cancer-related molecular mechanisms research (11 papers), Genomics and Phylogenetic Studies (7 papers), Autophagy in Disease and Therapy (6 papers), Aquaculture disease management and microbiota (6 papers), Gut microbiota and health (6 papers), Invertebrate Immune Response Mechanisms (5 papers) and RNA Research and Splicing (5 papers). The work is most often cited by research in Aging (170 citations), Cancer Research (242 citations), Molecular Biology (867 citations), Biological Psychiatry (29 citations) and Cellular and Molecular Neuroscience (209 citations). Xiaolan Fan has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Mingyao Yang, Deying Yang, Diyan Li, Uma Gaur, Weidong Le, Mingwang Zhang, Dehua Yang, Zhongxian Xu, Bo Zeng and Zhi He. Their work appears in journals such as International Journal of Molecular Sciences, Mechanisms of Ageing and Development, Aging, Frontiers in Genetics and PLoS ONE.

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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