Ying Wan

1.2k citations
26 papers · 947 · h-index 14

Impact in

Papers in

Ying Wan

24 papers receiving 938 citations

Peers

Ying Wan
Comparison fields: 5 of 103
  • Developmental Neuroscience 124
  • Pediatrics, Perinatology and Child Health 274
  • Food Science 150
  • Biomaterials 96
  • Endocrine and Autonomic Systems 48
Replace Yoshiko Takeuchi with:
Yoshiko Takeuchi Japan
Mohammad Naji Iran
Cindy Chen United States
Suneel Kumar India
Mahmood Barati Iran
Dajeong Kim South Korea
Fuquan Chen China
Martin Wolf Austria
Guodong Sun China
Zohreh Alizadeh Iran
Ying Wan relative to Yoshiko Takeuchi Japan Yoshiko Takeuchi's profile →
Citations per field
00.5×7.3×
Yoshiko Takeuchi · 1×
Citations per year

Countries citing papers authored by Ying Wan

Since Specialization
Citations

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

Fields of papers citing papers by Ying Wan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008262
2 2021136
3 2012107
4 201491
5 201069
6 200454
7 200336
8 200431
9 202328
10 201428
11 202322
12 202215
13 201614
14 202314
15 20179
16 20227
17 20225
18 20195
19 20244
20 20174

About Ying Wan

Ying Wan is a scholar working on Molecular Biology, Food Science, Materials Chemistry, Pediatrics, Perinatology and Child Health and Pulmonary and Respiratory Medicine, having authored 26 papers that have together received 947 indexed citations. Recurring topics across this work include Proteins in Food Systems (5 papers), Pickering emulsions and particle stabilization (4 papers), Conducting polymers and applications (2 papers), Polysaccharides Composition and Applications (2 papers), Neonatal and fetal brain pathology (2 papers), Electrospun Nanofibers in Biomedical Applications (2 papers), Plant Pathogenic Bacteria Studies (2 papers) and RNA modifications and cancer (2 papers). The work is most often cited by research in Developmental Neuroscience (124 citations), Pediatrics, Perinatology and Child Health (274 citations), Food Science (150 citations), Biomaterials (96 citations) and Endocrine and Autonomic Systems (48 citations). Ying Wan has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Zhengxing Chen, Art Riddle, Stephen A. Back, Ren Wang, Xi Gong, Tao Wang, Wei Feng, Larry S. Sherman, Kristen N. Segovia and Ning Luo. Their work appears in journals such as Annals of Neurology, Proceedings of the National Academy of Sciences, Infection and Drug Resistance, International Journal of Biological Macromolecules and Food Chemistry.

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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