Thai Dinh

15 papers receiving 973 citations

Thai Dinh's Hit Papers

GFRAL is the receptor for GDF15 and the ligand promotes weight loss in mice and nonhuman primates 2017 · 549 citations
5490+3+6Years since publication100200300400500

Peers

Thai Dinh
Comparison fields: 5 of 83
  • Rheumatology 407
  • Physiology 360
  • Sensory Systems 52
  • Cellular and Molecular Neuroscience 160
  • Immunology 168
Replace Nicola Rizzuto with:
Nicola Rizzuto Italy
James Meixiong United States
David Coman Australia
Mohammad K. Sharief United Kingdom
Emma L. Braine Australia
Yasmin Husaini Australia
Tsuyoshi Ishida Japan
Denise Cassandrini Italy
Christine Barnérias France
Melissa McBride United States
Thai Dinh relative to Nicola Rizzuto Italy Nicola Rizzuto's profile →
Citations per field
00.5×
Nicola Rizzuto · 1×
Citations per year

Countries citing papers authored by Thai Dinh

Since Specialization
Citations

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

Fields of papers citing papers by Thai Dinh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

16 of 16 papers shown
#Work
1
GFRAL is the receptor for GDF15 and the ligand promotes weight loss in mice and nonhuman primates
Hit paper breakdown →
2017549
2 1996102
3 200666
4 199453
5 199938
6 199334
7 201029
8 201227
9 199126
10 199824
11 199120
12 199411
13 20089
14 19897
15 19961
16 20170

About Thai Dinh

Thai Dinh is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging, Cell Biology, Physiology and Biomedical Engineering, having authored 16 papers that have together received 996 indexed citations. Recurring topics across this work include Cellular transport and secretion (4 papers), Monoclonal and Polyclonal Antibodies Research (4 papers), Glycosylation and Glycoproteins Research (2 papers), T-cell and B-cell Immunology (2 papers), Biotin and Related Studies (2 papers), Ion Channels and Receptors (2 papers), Asthma and respiratory diseases (2 papers) and Respiratory and Cough-Related Research (2 papers). The work is most often cited by research in Rheumatology (407 citations), Physiology (360 citations), Sensory Systems (52 citations), Cellular and Molecular Neuroscience (160 citations) and Immunology (168 citations). Thai Dinh has collaborated with scholars based in United States, Italy and Germany. Frequent co-authors include Michael J. Hunter, Shannon E. Mullican, Anthony A. Armstrong, Xiefan Lin‐Schmidt, Jose A. Chavez, Cassandre Cavanaugh, Victoria J. South, Chen‐Ni Chin, Shamina M. Rangwala and Jennifer L. Furman. Their work appears in journals such as Hypertension, BioTechniques, Regulatory Peptides, Journal of Applied Physiology and Biological 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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