Van V. Vu

47 papers receiving 2.0k citations

Van V. Vu's Hit Papers

Autodock Vina Adopts More Accurate Binding Poses but Autodock4 Forms Better Binding Affinity 2019 · 300 citations
3000+2+4Years since publication100200300

Peers

Van V. Vu
Comparison fields: 5 of 122
  • Biotechnology 314
  • Computational Theory and Mathematics 429
  • Inorganic Chemistry 309
  • Pollution 153
  • Molecular Biology 917
Replace Hong Lin Zhai with:
Hong Lin Zhai China
Karine Auclair Canada
Jiahai Zhou China
Jatinder Singh India
Rainer Schobert Germany
Zhenjiang Li China
Shana J. Sturla Switzerland
Warren R. J. D. Galloway United Kingdom
Helen S. Toogood United Kingdom
Zhoutong Sun China
Van V. Vu relative to Hong Lin Zhai China Hong Lin Zhai's profile →
Citations per field
00.5×3.2×
Hong Lin Zhai · 1×
Citations per year

Countries citing papers authored by Van V. Vu

Since Specialization
Citations

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

Fields of papers citing papers by Van V. Vu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Van V. Vu. 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 Van V. Vu. The network helps show where Van V. Vu may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Autodock Vina Adopts More Accurate Binding Poses but Autodock4 Forms Better Binding Affinity
Hit paper breakdown →
2019300
2 2015224
3 2014209
4 2013183
5 2020119
6 2020114
7 200997
8 201569
9 201958
10 202147
11 201847
12 201236
13 202035
14 201934
15 201930
16 202028
17 201627
18 201927
19 200927
20 201725

About Van V. Vu

Van V. Vu is a scholar working on Molecular Biology, Computational Theory and Mathematics, Biomedical Engineering, Inorganic Chemistry and Physiology, having authored 50 papers that have together received 2.0k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (17 papers), Computational Drug Discovery Methods (15 papers), Alzheimer's disease research and treatments (7 papers), Metal-Catalyzed Oxygenation Mechanisms (7 papers), Biofuel production and bioconversion (7 papers), Enzyme Production and Characterization (5 papers), Enzyme-mediated dye degradation (4 papers) and SARS-CoV-2 and COVID-19 Research (4 papers). The work is most often cited by research in Biotechnology (314 citations), Computational Theory and Mathematics (429 citations), Inorganic Chemistry (309 citations), Pollution (153 citations) and Molecular Biology (917 citations). Van V. Vu has collaborated with scholars based in Vietnam, United States and United Kingdom. Frequent co-authors include Sơn Tùng Ngô, Michael A. Marletta, William T. Beeson, Elise A. Span, Christopher M. Phillips, Trung Hai Nguyen, Phạm Minh Quân, Pham Cam Nam, Lawrence Que and Erik R. Farquhar. Their work appears in journals such as RSC Advances, The Journal of Physical Chemistry B, Journal of Chemical Information and Modeling, ACS Omega and Journal of the American Chemical Society.

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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