Yangfan Wang

2.6k citations
87 papers · 1.3k · h-index 23

Impact in

Papers in

    • Neural Networks Stability and Synchronization 19
    • Genetic and phenotypic traits in livestock 17
    • Genetic Mapping and Diversity in Plants and Animals 9
    • Genetic diversity and population structure 9

Yangfan Wang

79 papers receiving 1.3k citations

Peers

Yangfan Wang
Comparison fields: 5 of 126
  • Aquatic Science 177
  • Computer Networks and Communications 329
  • Ophthalmology 100
  • Statistical and Nonlinear Physics 157
  • Modeling and Simulation 44
Replace Patrik D’haeseleer with:
Patrik D’haeseleer United States
Hideo Matsuda Japan
Jianqiang Sun China
Johannes Köster Germany
Qinglin Wang China
Yuanmei Wang China
Qizhen Xiao China
Tun‐Wen Pai Taiwan
Miguel Reboiro‐Jato Spain
Yangfan Wang relative to Patrik D’haeseleer United States Patrik D’haeseleer's profile →
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Citations per year

Countries citing papers authored by Yangfan Wang

Since Specialization
Citations

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

Fields of papers citing papers by Yangfan Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 87 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013118
2 201968
3 200866
4 201665
5 201549
6 201645
7 201845
8 202441
9 201841
10 202441
11 200740
12 201437
13 201337
14 201536
15 202434
16 201532
17 201829
18 202228
19 201324
20 202223

About Yangfan Wang

Yangfan Wang is a scholar working on Computer Networks and Communications, Genetics, Molecular Biology, Artificial Intelligence and Aquatic Science, having authored 87 papers that have together received 1.3k indexed citations. Recurring topics across this work include Neural Networks Stability and Synchronization (19 papers), Genetic and phenotypic traits in livestock (17 papers), Neural Networks and Applications (11 papers), Genetic Mapping and Diversity in Plants and Animals (9 papers), Genetic diversity and population structure (9 papers), Advanced Memory and Neural Computing (6 papers), Marine Bivalve and Aquaculture Studies (6 papers) and stochastic dynamics and bifurcation (6 papers). The work is most often cited by research in Aquatic Science (177 citations), Computer Networks and Communications (329 citations), Ophthalmology (100 citations), Statistical and Nonlinear Physics (157 citations) and Modeling and Simulation (44 citations). Yangfan Wang has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Linshan Wang, Ping Lin, Zhenmin Bao, Guangrong Ji, Tengda Wei, Emanuele Trucco, Shi Wang, Yangping Li, Zhe Zhang and Xiaoli Hu. Their work appears in journals such as Aquaculture, Frontiers in Genetics, Journal of the American Chemical Society, Marine Biotechnology and Scientific Reports.

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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