Shu Fang

2.6k citations
91 papers · 1.9k indexed · h-index 24
Topics
Hematopoietic Stem Cell Transplantation (8 papers)Genetic diversity and population structure (8 papers)Adipose Tissue and Metabolism (6 papers)
Partner nations
ChinaUnited StatesJapan

In The Last Decade

Shu Fang

85 papers receiving 1.8k citations

Peers

Shu Fang
Comparison fields: 5 of 145
  • Molecular Biology 691
  • Genetics 626
  • Plant Science 234
  • Cellular and Molecular Neuroscience 206
  • Ecology, Evolution, Behavior and Systematics 202
Replace Jing He with:
Jing He China
Charlotte Lécureuil France
Gabriel Gutiérrez Spain
Yemin Lan United States
Michael R. Garvin United States
Shinichi Miyagawa Japan
Christopher D. Brown United States
Robert H. Podolsky United States
Paweł Grzmil Poland
Runsheng Li China
Shu Fang relative to Jing He China Jing He's profile →
Citations per field
00.5×3.0×
Jing He · 1×
Citations per year

Countries citing papers authored by Shu Fang

Since Specialization
Citations

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

Fields of papers citing papers by Shu Fang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shu Fang

This figure shows the co-authorship network connecting the top 25 collaborators of Shu Fang. A scholar is included among the top collaborators of Shu Fang 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 Shu Fang. Shu Fang 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
#WorkIndexed citations
1 9
2 1
3 3
4 1
5 1
6 1
7 3
8 3
9 7
10 3
11 2
12 1
13 24
14 11
15 16
16 53
17
Correlation of genetic polymorphisms of matrix metalloproteinase-1 with non-small cell lung carcinoma
1
18 16
19 73
20
Study of a novel type absorbable wound hemostaic sealant on animal hemostatic effect
1

About Shu Fang

Shu Fang is a scholar working on Hematology, Genetics and Immunology, having authored 91 papers that have together received 1.9k indexed citations. Recurring topics across this work include Hematopoietic Stem Cell Transplantation (8 papers), Genetic diversity and population structure (8 papers) and Adipose Tissue and Metabolism (6 papers). The work is most often cited by research in Genetics (626 citations), Insect Science (167 citations) and Hematology (134 citations). Shu Fang has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Chung‐I Wu, Aya Takahashi, Hiroshi Kobayashi, David A. Turissini, Toshihiko Terao, Michael H. Kohn, Jinyi Li, Zhaochu Hu, Junfeng Qu and Zhong Zhang. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Communications 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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