Fei-Da Ni

704 citations
12 papers · 466 · 1 hit paper · h-index 7

Impact in

Papers in

Fei-Da Ni

12 papers receiving 461 citations

Fei-Da Ni's Hit Papers

Multiple signaling pathways in Sertoli cells: recent findings in spermatogenesis 2019 · 184 citations
1840+2+4Years since publication50100150

Peers

Fei-Da Ni
Comparison fields: 5 of 75
  • Reproductive Medicine 201
  • Obstetrics and Gynecology 47
  • Cancer Research 73
  • Public Health, Environmental and Occupational Health 103
  • Immunology 69
Replace Ilana R. Bernstein with:
Ilana R. Bernstein Australia
Marcin Chruściel Poland
Jitu W. George United States
Alex Muñoz Chile
Qiliang Xin China
Feixue Li China
Dongzhi Yuan China
Lianwen Zheng China
Zhiwen Lai China
Xue‐Shan Ma China
Fei-Da Ni relative to Ilana R. Bernstein Australia Ilana R. Bernstein's profile →
Citations per field
00.5×1.7×
Ilana R. Bernstein · 1×
Citations per year

Countries citing papers authored by Fei-Da Ni

Since Specialization
Citations

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

Fields of papers citing papers by Fei-Da Ni

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fei-Da Ni. 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 Fei-Da Ni. The network helps show where Fei-Da Ni may publish in the future.

Co-authors

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

All Works

12 of 12 papers shown
#Work
1
Multiple signaling pathways in Sertoli cells: recent findings in spermatogenesis
Hit paper breakdown →
2019184
2 202290
3 201976
4 202247
5 202036
6 20237
7 20237
8 20206
9 20245
10 20234
11 20242
12 20242

About Fei-Da Ni

Fei-Da Ni is a scholar working on Reproductive Medicine, Public Health, Environmental and Occupational Health, Molecular Biology, Obstetrics and Gynecology and Immunology, having authored 12 papers that have together received 466 indexed citations. Recurring topics across this work include Reproductive Biology and Fertility (6 papers), Sperm and Testicular Function (5 papers), Endometriosis Research and Treatment (4 papers), Reproductive System and Pregnancy (3 papers), Gynecological conditions and treatments (2 papers), Uterine Myomas and Treatments (2 papers), Ovarian function and disorders (2 papers) and Genetic Associations and Epidemiology (1 paper). The work is most often cited by research in Reproductive Medicine (201 citations), Obstetrics and Gynecology (47 citations), Cancer Research (73 citations), Public Health, Environmental and Occupational Health (103 citations) and Immunology (69 citations). Fei-Da Ni has collaborated with scholars based in China, Thailand and United States. Frequent co-authors include Wan-Xi Yang, Shuang-Li Hao, Xiaohang Ye, Dan Zhang, Siwen Wang, Ruixue Chen, Chuan Chen, Xiao Xu, Xiao Sun and Jianpeng Chen. Their work appears in journals such as Gene, Biology of Reproduction, The American Journal of Human Genetics, Cell Death and Disease and Nature 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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