Ying‐Ta Wu

1.7k citations
43 papers · 1.4k · h-index 19

Impact in

Papers in

    • Glycosylation and Glycoproteins Research 9
    • Chemical Synthesis and Analysis 6
    • Protein Structure and Dynamics 4
    • RNA and protein synthesis mechanisms 4
    • Biochemical and Structural Characterization 3
    • Carbohydrate Chemistry and Synthesis 10

Ying‐Ta Wu

42 papers receiving 1.4k citations

Peers

Ying‐Ta Wu
Comparison fields: 5 of 120
  • Organic Chemistry 397
  • Infectious Diseases 236
  • Computational Theory and Mathematics 179
  • Molecular Biology 696
  • Immunology 188
Replace Ingrid Choong with:
Ingrid Choong United States
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Ying‐Ta Wu relative to Ingrid Choong United States Ingrid Choong's profile →
Citations per field
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Ingrid Choong · 1×
Citations per year

Countries citing papers authored by Ying‐Ta Wu

Since Specialization
Citations

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

Fields of papers citing papers by Ying‐Ta Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005154
2 2021130
3 2006105
4 2006100
5 200896
6 201094
7 200077
8 201172
9 201560
10 201057
11 201635
12 200630
13 200728
14 201328
15 199927
16 200125
17 200620
18 201320
19 199818
20 201317

About Ying‐Ta Wu

Ying‐Ta Wu is a scholar working on Molecular Biology, Organic Chemistry, Epidemiology, Oncology and Computational Theory and Mathematics, having authored 43 papers that have together received 1.4k indexed citations. Recurring topics across this work include Carbohydrate Chemistry and Synthesis (10 papers), Glycosylation and Glycoproteins Research (9 papers), Chemical Synthesis and Analysis (6 papers), Computational Drug Discovery Methods (5 papers), Influenza Virus Research Studies (5 papers), Protein Structure and Dynamics (4 papers), RNA and protein synthesis mechanisms (4 papers) and Biochemical and Structural Characterization (3 papers). The work is most often cited by research in Organic Chemistry (397 citations), Infectious Diseases (236 citations), Computational Theory and Mathematics (179 citations), Molecular Biology (696 citations) and Immunology (188 citations). Ying‐Ta Wu has collaborated with scholars based in Taiwan, United States and United Kingdom. Frequent co-authors include Chi‐Huey Wong, Shui-Tein Chen, Chun‐Ming Huang, Wei‐Chieh Cheng, Ting-Jen Rachel Cheng, Chih‐Jung Kuo, Ming‐Daw Tsai, Pi‐Hui Liang, Chung‐Yi Wu and Shyh‐Fong Chen. Their work appears in journals such as ACS Chemical Biology, Proceedings of the National Academy of Sciences, Bioorganic & Medicinal Chemistry, Chemical Communications and Bioorganic & Medicinal Chemistry Letters.

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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