Ling‐Hsien Tu

1.9k citations
40 papers · 1.6k · h-index 18

Impact in

  • Physiology top 2%
    • Alzheimer's disease research and treatments
    • Supramolecular Self-Assembly in Materials

Papers in

    • Alzheimer's disease research and treatments 30
    • Protein Structure and Dynamics 5
    • Prion Diseases and Protein Misfolding 4

Ling‐Hsien Tu

39 papers receiving 1.6k citations

Peers

Ling‐Hsien Tu
Comparison fields: 5 of 93
  • Physiology 1.0k
  • Biomaterials 262
  • Clinical Biochemistry 103
  • Cell Biology 215
  • Molecular Biology 874
Replace Michele F. M. Sciacca with:
Michele F. M. Sciacca Italy
Zhefeng Guo United States
Yair Porat Israel
Yilin Yan United States
Laura Masino United Kingdom
Angela D. Williams United States
Larissa A. Munishkina United States
Masafumi Sakono Japan
Annett Boeddrich Germany
Natàlia Carulla Spain
Ling‐Hsien Tu relative to Michele F. M. Sciacca Italy Michele F. M. Sciacca's profile →
Citations per field
00.5×
Michele F. M. Sciacca · 1×
Citations per year

Countries citing papers authored by Ling‐Hsien Tu

Since Specialization
Citations

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

Fields of papers citing papers by Ling‐Hsien Tu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ling‐Hsien Tu. 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 Ling‐Hsien Tu. The network helps show where Ling‐Hsien Tu may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014238
2 2015200
3 2013152
4 2016132
5 2013130
6 2012113
7 201172
8 202069
9 201761
10 201452
11 201551
12 201734
13 201431
14 201928
15 200519
16 201918
17 202217
18 201517
19 200417
20 201815

About Ling‐Hsien Tu

Ling‐Hsien Tu is a scholar working on Physiology, Molecular Biology, Biomaterials, Oncology and Cell Biology, having authored 40 papers that have together received 1.6k indexed citations. Recurring topics across this work include Alzheimer's disease research and treatments (30 papers), Supramolecular Self-Assembly in Materials (8 papers), Endoplasmic Reticulum Stress and Disease (5 papers), Protein Structure and Dynamics (5 papers), Cholinesterase and Neurodegenerative Diseases (4 papers), Prion Diseases and Protein Misfolding (4 papers), Pancreatic function and diabetes (3 papers) and Computational Drug Discovery Methods (3 papers). The work is most often cited by research in Physiology (1.0k citations), Biomaterials (262 citations), Clinical Biochemistry (103 citations), Cell Biology (215 citations) and Molecular Biology (874 citations). Ling‐Hsien Tu has collaborated with scholars based in Taiwan, United States and United Kingdom. Frequent co-authors include Daniel P. Raleigh, Ping Cao, Andisheh Abedini, Ann Marie Schmidt, Sheena E. Radford, Alison E. Ashcroft, Lydia Young, Xiaoxue Zhang, Amy G. Wong and Rachel Mahood. Their work appears in journals such as Biochemistry, Biochimie, Biophysical Journal, The Journal of Physical Chemistry B and Organometallics.

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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