Thin Nguyen

80 papers receiving 1.9k citations

Thin Nguyen's Hit Papers

GraphDTA: predicting drug–target binding affinity with graph neural networks 2020 · 718 citations
7180+2+4Years since publication200400600

Peers

Thin Nguyen
Comparison fields: 5 of 137
  • Computational Theory and Mathematics 718
  • Applied Psychology 158
  • Social Psychology 372
  • Artificial Intelligence 428
  • Experimental and Cognitive Psychology 142
Replace Kevin Bretonnel Cohen with:
Kevin Bretonnel Cohen United States
Bo Xu China
Jérôme Azé France
Philippe Lenca France
Arman Cohan United States
Sandra Bringay France
Angus Roberts United Kingdom
David L. Dowe Australia
Liang Yang China
Thin Nguyen relative to Kevin Bretonnel Cohen United States Kevin Bretonnel Cohen's profile →
Citations per field
00.5×7.8×
Kevin Bretonnel Cohen · 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 90 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 →
2020718
2 2014176
3 2017146
4 2021115
5 201560
6 202155
7 201652
8 201730
9 201228
10 202126
11 201524
12 201722
13 201321
14 202220
15 201520
16 201420
17 201020
18 201318
19 201116
20 201515

About Thin Nguyen

Thin Nguyen is a scholar working on Artificial Intelligence, Social Psychology, Statistical and Nonlinear Physics, Epidemiology and Molecular Biology, having authored 90 papers that have together received 1.9k indexed citations. Recurring topics across this work include Sentiment Analysis and Opinion Mining (26 papers), Mental Health via Writing (25 papers), Complex Network Analysis Techniques (18 papers), Data-Driven Disease Surveillance (7 papers), Mental Health Research Topics (7 papers), Topic Modeling (6 papers), Computational Drug Discovery Methods (6 papers) and Recommender Systems and Techniques (6 papers). The work is most often cited by research in Computational Theory and Mathematics (718 citations), Applied Psychology (158 citations), Social Psychology (372 citations), Artificial Intelligence (428 citations) and Experimental and Cognitive Psychology (142 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, Mark Larsen and Bridianne O’Dea. Their work appears in journals such as Knowledge and Information Systems, IEEE/ACM Transactions on Computational Biology and Bioinformatics, PLoS ONE, Bioinformatics and IEEE Transactions on Affective Computing.

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.

Explore authors with similar magnitude of impact