Thin Nguyen

61 papers receiving 1.5k citations

Thin Nguyen's Hit Papers

GraphDTA: predicting drug–target binding affinity with graph neural networks 2020 · 629 citations
6290+2+4Years since publication200400600

Peers

Thin Nguyen
Comparison fields: 5 of 134
  • Computational Theory and Mathematics 662
  • Applied Psychology 148
  • Social Psychology 301
  • Artificial Intelligence 344
  • Molecular Biology 718
Replace Bo Xu with:
Bo Xu China
Anthony Gitter United States
Igor Zwir United States
Yaoyun Zhang United States
Ramakanth Kavuluru United States
Jay I. Myung United States
David L. Dowe Australia
Robert Matthews United Kingdom
Yu Shi Australia
Thin Nguyen relative to Bo Xu China Bo Xu's profile →
Citations per field
00.5×6.0×
Bo Xu · 1×
Citations per year

Countries citing papers authored by Thin Nguyen

Since Specialization
Citations

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

Fields of papers citing papers by Thin Nguyen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 65 papers — load more, or switch the sort, to bring in the rest.

#Work
1
GraphDTA: predicting drug–target binding affinity with graph neural networks
Hit paper breakdown →
2020629
2 2014159
3 2017127
4 2021107
5 201554
6 202152
7 201647
8 201728
9 201228
10 202124
11 201721
12 201520
13 201318
14 201517
15 202215
16 201514
17 201314
18 201913
19 201313
20 201712

About Thin Nguyen

Thin Nguyen is a scholar working on Artificial Intelligence, Social Psychology, Statistical and Nonlinear Physics, Molecular Biology and Epidemiology, having authored 65 papers that have together received 1.6k indexed citations. Recurring topics across this work include Mental Health via Writing (16 papers), Sentiment Analysis and Opinion Mining (16 papers), Complex Network Analysis Techniques (15 papers), Data-Driven Disease Surveillance (7 papers), Computational Drug Discovery Methods (6 papers), Bioinformatics and Genomic Networks (6 papers), Topic Modeling (6 papers) and Recommender Systems and Techniques (4 papers). The work is most often cited by research in Computational Theory and Mathematics (662 citations), Applied Psychology (148 citations), Social Psychology (301 citations), Artificial Intelligence (344 citations) and Molecular Biology (718 citations). Thin Nguyen has collaborated with scholars based in Australia, Vietnam and United States. Frequent co-authors include Svetha Venkatesh, Dinh Phung, Tri Minh Nguyen, Thomas P. Quinn, Thuc Duy Le, Hang Le, Michael Berk, Duc‐Hau Le, Bridianne O’Dea and Helen Christensen. Their work appears in journals such as Knowledge and Information Systems, IEEE/ACM Transactions on Computational Biology and Bioinformatics, PLoS ONE, Bioinformatics and American Journal of Medical Genetics Part B Neuropsychiatric Genetics.

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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