Ling‐Hsien Tu

1.9k total citations
40 papers, 1.6k citations indexed

About

Ling‐Hsien Tu is a scholar working on Physiology, Molecular Biology and Biomaterials. According to data from OpenAlex, Ling‐Hsien Tu has authored 40 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Physiology, 17 papers in Molecular Biology and 9 papers in Biomaterials. Recurrent topics in Ling‐Hsien Tu's work include Alzheimer's disease research and treatments (30 papers), Supramolecular Self-Assembly in Materials (8 papers) and Protein Structure and Dynamics (5 papers). Ling‐Hsien Tu is often cited by papers focused on Alzheimer's disease research and treatments (30 papers), Supramolecular Self-Assembly in Materials (8 papers) and Protein Structure and Dynamics (5 papers). Ling‐Hsien Tu collaborates with scholars based in Taiwan, United States and United Kingdom. Ling‐Hsien Tu's co-authors include Daniel P. Raleigh, Ping Cao, Andisheh Abedini, Ann Marie Schmidt, Alison E. Ashcroft, Lydia Young, Sheena E. Radford, Xiaoxue Zhang, Amy G. Wong and Janet C. Saunders and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Journal of Biological Chemistry.

In The Last Decade

Ling‐Hsien Tu

39 papers receiving 1.6k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ling‐Hsien Tu Taiwan 18 1.0k 874 262 215 194 40 1.6k
Michele F. M. Sciacca Italy 23 1.2k 1.2× 1.1k 1.3× 312 1.2× 199 0.9× 103 0.5× 47 1.8k
Yuxi Lin South Korea 17 749 0.7× 800 0.9× 180 0.7× 93 0.4× 72 0.4× 57 1.4k
Yair Porat Israel 8 1.1k 1.1× 943 1.1× 467 1.8× 105 0.5× 50 0.3× 9 1.7k
Jonathan D. Lowenson United States 18 1.1k 1.1× 1.4k 1.6× 100 0.4× 132 0.6× 129 0.7× 26 2.4k
Andisheh Abedini United States 27 2.1k 2.1× 1.8k 2.0× 526 2.0× 498 2.3× 536 2.8× 35 3.1k
Ivana Sirangelo Italy 24 622 0.6× 837 1.0× 98 0.4× 231 1.1× 44 0.2× 63 1.5k
Sean Chia United Kingdom 21 916 0.9× 929 1.1× 221 0.8× 133 0.6× 43 0.2× 46 1.5k
Masafumi Sakono Japan 18 597 0.6× 791 0.9× 148 0.6× 213 1.0× 38 0.2× 56 1.4k
Deborah J. Tew Australia 26 1.8k 1.8× 1.0k 1.2× 211 0.8× 136 0.6× 29 0.1× 35 2.6k
Mihaela Necula United States 15 1.9k 1.9× 1.2k 1.4× 220 0.8× 197 0.9× 25 0.1× 19 2.4k

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-authorship network of co-authors of Ling‐Hsien Tu

This figure shows the co-authorship network connecting the top 25 collaborators of Ling‐Hsien Tu. A scholar is included among the top collaborators of Ling‐Hsien Tu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ling‐Hsien Tu. Ling‐Hsien Tu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Huang, Shing‐Jong, et al.. (2025). Oligomeric Protein Complexes Formed by Beta Amyloid Peptides and Their Molecular Associates. Chemistry - A European Journal. 31(38). e202501099–e202501099. 1 indexed citations
2.
3.
Tu, Ling‐Hsien, et al.. (2023). TPE conjugated islet amyloid polypeptide probe for detection of peptide oligomers. Biophysical Chemistry. 304. 107129–107129. 2 indexed citations
4.
Hsu, Chia-Chien, Yilun Chen, Wei‐Min Liu, et al.. (2023). Synthesis of Fe3O4-Chlorophyllin Nanoparticles for Preventing Amyloid Formation by Human Calcitonin. ACS Applied Nano Materials. 6(13). 12598–12608. 1 indexed citations
5.
Tu, Ling‐Hsien, et al.. (2023). Investigating the inhibitory property of DM hCT on hCT fibrillization via its relevant peptide fragments. Protein Science. 32(8). e4711–e4711. 6 indexed citations
6.
Wu, Yishan, et al.. (2022). Site specific NMR characterization of abeta-40 oligomers cross seeded by abeta-42 oligomers. Chemical Science. 13(29). 8526–8535. 17 indexed citations
7.
Tsai, Yu‐Ting, et al.. (2022). The Role of Aldehyde‐Functionalized Crosslinkers on the Property of Chitosan Hydrogels. Macromolecular Bioscience. 22(5). e2100477–e2100477. 14 indexed citations
8.
Hsu, Chia-Chien, I‐Ren Lee, Yuxin Shen, et al.. (2022). An environmentally sensitive molecular rotor as a NIR fluorescent probe for the detection of islet amyloid polypeptide. Talanta. 254. 124130–124130. 8 indexed citations
9.
Chen, Ting-Wei, et al.. (2022). Tyrosine 12 of human calcitonin modulates its amyloid formation, membrane binding, and bioactivity. Biochimie. 197. 121–129. 7 indexed citations
10.
Fan, Hsiu‐Fang, et al.. (2021). Exploring the Impact of Glyoxal Glycation on β-Amyloid Peptide (Aβ) Aggregation in Alzheimer’s Disease. The Journal of Physical Chemistry B. 125(21). 5559–5571. 6 indexed citations
11.
Shih, Yao‐Hsiang, et al.. (2020). TDP-43 interacts with amyloid-β, inhibits fibrillization, and worsens pathology in a model of Alzheimer’s disease. Nature Communications. 11(1). 5950–5950. 69 indexed citations
12.
Chen, Yun‐Wen, et al.. (2019). Protein Glycation by Glyoxal Promotes Amyloid Formation by Islet Amyloid Polypeptide. Biophysical Journal. 116(12). 2304–2313. 28 indexed citations
13.
Tu, Ling‐Hsien, et al.. (2018). Rationally designed divalent caffeic amides inhibit amyloid-β fibrillization, induce fibril dissociation, and ameliorate cytotoxicity. European Journal of Medicinal Chemistry. 158. 393–404. 15 indexed citations
14.
Abedini, Andisheh, Annette Plesner, Ping Cao, et al.. (2016). Time-resolved studies define the nature of toxic IAPP intermediates, providing insight for anti-amyloidosis therapeutics. eLife. 5. 132 indexed citations
15.
Meier, Daniel T., Ling‐Hsien Tu, Sakeneh Zraika, et al.. (2015). Matrix Metalloproteinase-9 Protects Islets from Amyloid-induced Toxicity. Journal of Biological Chemistry. 290(51). 30475–30485. 17 indexed citations
16.
Tu, Ling‐Hsien, Arnaldo L. Serrano, Martin T. Zanni, & Daniel P. Raleigh. (2014). Mutational Analysis of Preamyloid Intermediates: The Role of His-Tyr Interactions in Islet Amyloid Formation. Biophysical Journal. 106(7). 1520–1527. 31 indexed citations
17.
Young, Lydia, Janet C. Saunders, Rachel Mahood, et al.. (2014). Screening and classifying small-molecule inhibitors of amyloid formation using ion mobility spectrometry–mass spectrometry. Nature Chemistry. 7(1). 73–81. 238 indexed citations
18.
Cao, Ping, Peter Marek, Vadim Patsalo, et al.. (2013). Islet amyloid: From fundamental biophysics to mechanisms of cytotoxicity. FEBS Letters. 587(8). 1106–1118. 152 indexed citations
19.
Tu, Ling‐Hsien & Daniel P. Raleigh. (2012). Role of Aromatic Interactions in Amyloid Formation by Islet Amyloid Polypeptide. Biochemistry. 52(2). 333–342. 113 indexed citations
20.
Cao, Ping, Ling‐Hsien Tu, Andisheh Abedini, et al.. (2011). Sensitivity of Amyloid Formation by Human Islet Amyloid Polypeptide to Mutations at Residue 20. Journal of Molecular Biology. 421(2-3). 282–295. 72 indexed citations

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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