Tomohide Masuda

1.4k total citations · 1 hit paper
10 papers, 744 citations indexed

About

Tomohide Masuda is a scholar working on Materials Chemistry, Molecular Biology and Computational Theory and Mathematics. According to data from OpenAlex, Tomohide Masuda has authored 10 papers receiving a total of 744 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Materials Chemistry, 5 papers in Molecular Biology and 5 papers in Computational Theory and Mathematics. Recurrent topics in Tomohide Masuda's work include Computational Drug Discovery Methods (5 papers), Protein Structure and Dynamics (3 papers) and Machine Learning in Materials Science (3 papers). Tomohide Masuda is often cited by papers focused on Computational Drug Discovery Methods (5 papers), Protein Structure and Dynamics (3 papers) and Machine Learning in Materials Science (3 papers). Tomohide Masuda collaborates with scholars based in Japan, United States and India. Tomohide Masuda's co-authors include David Ryan Koes, Matthew Ragoza, Paul Francoeur, Jocelyn Sunseri, Rishal Aggarwal, Rocco Meli, Andrew T. McNutt, I. M. Snyder, Satoshi Yabushita and Atsushi Nakajima and has published in prestigious journals such as Scientific Reports, The Journal of Physical Chemistry A and Chemical Science.

In The Last Decade

Tomohide Masuda

9 papers receiving 722 citations

Hit Papers

GNINA 1.0: molecular docking with deep learning 2021 2026 2022 2024 2021 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. GNINA 1.0: molecular docking with deep learning
    2021 397 citations Andrew T. McNutt, Paul Francoeur et al. Journal of Cheminformatics profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tomohide Masuda Japan 6 495 476 246 79 67 10 744
Rocco Meli United Kingdom 6 420 0.8× 363 0.8× 152 0.6× 57 0.7× 55 0.8× 8 622
John W. Mayfield United States 3 542 1.1× 581 1.2× 207 0.8× 89 1.1× 102 1.5× 3 936
Christof Gerlach Germany 9 421 0.9× 384 0.8× 257 1.0× 91 1.2× 51 0.8× 15 704
Tobias Fink Switzerland 4 329 0.7× 432 0.9× 225 0.9× 102 1.3× 59 0.9× 5 603
James L. Melville United Kingdom 15 378 0.8× 422 0.9× 171 0.7× 130 1.6× 77 1.1× 23 775
Matthias Zentgraf Germany 11 511 1.0× 467 1.0× 265 1.1× 129 1.6× 100 1.5× 14 946
Isha Singh United States 10 666 1.3× 417 0.9× 181 0.7× 105 1.3× 82 1.2× 14 901
Wen Torng United States 7 632 1.3× 715 1.5× 337 1.4× 70 0.9× 74 1.1× 7 1.0k
Zhixiong Zhao China 14 780 1.6× 610 1.3× 225 0.9× 139 1.8× 200 3.0× 30 1.1k
Nikolay Savchuk United States 16 460 0.9× 569 1.2× 134 0.5× 152 1.9× 65 1.0× 31 911

Countries citing papers authored by Tomohide Masuda

Since Specialization
Citations

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

Fields of papers citing papers by Tomohide Masuda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tomohide Masuda

This figure shows the co-authorship network connecting the top 25 collaborators of Tomohide Masuda. A scholar is included among the top collaborators of Tomohide Masuda 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 Tomohide Masuda. Tomohide Masuda is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

10 of 10 papers shown
1.
Fujino, K., Shunsuke Murai, Tomohide Masuda, et al.. (2025). Nonwoven fabric coated with cerium oxide nanoparticles for viral inactivation and transmission Inhibition. Scientific Reports. 15(1). 10340–10340. 1 indexed citations
2.
Masuda, Tomohide, Chiduru Watanabe, Koichiro Kato, et al.. (2025). Quantitative Structure–Activity Relationships for Human Galectin-3 Inhibitors: Insights from Quantum Chemical Interaction Energy Terms. Journal of Chemical Information and Modeling. 65(12). 6287–6297.
3.
Fujino, K., Shunsuke Murai, Tomohide Masuda, et al.. (2024). Efficient inactivation of influenza virus through adsorption of nanoceria and its oxidative power. Chemistry Letters. 53(7). 1 indexed citations
4.
Ragoza, Matthew, Tomohide Masuda, & David Ryan Koes. (2022). Generating 3D molecules conditional on receptor binding sites with deep generative models. Chemical Science. 13(9). 2701–2713. 111 indexed citations
5.
McNutt, Andrew T., Paul Francoeur, Rishal Aggarwal, et al.. (2021). GNINA 1.0: molecular docking with deep learning. Journal of Cheminformatics. 13(1). 43–43. 397 indexed citations breakdown →
6.
Kato, Koichiro, Tomohide Masuda, Chiduru Watanabe, et al.. (2020). High-Precision Atomic Charge Prediction for Protein Systems Using Fragment Molecular Orbital Calculation and Machine Learning. Journal of Chemical Information and Modeling. 60(7). 3361–3368. 31 indexed citations
7.
Francoeur, Paul, et al.. (2020). Three-Dimensional Convolutional Neural Networks and a Cross-Docked Data Set for Structure-Based Drug Design. Journal of Chemical Information and Modeling. 60(9). 4200–4215. 175 indexed citations
8.
Esaki, Tsuyoshi, Kazutoshi Takahashi, Reiko Watanabe, et al.. (2020). Open Innovation Platform using Cloud-based Applications and Collaborative Space: A Case Study of Solubility Prediction Model Development. 20(0). 5–18. 1 indexed citations
9.
Masuda, Tomohide, et al.. (2016). Theoretical Study on the Photoelectron Spectra of Ln(COT)2–: Lanthanide Dependence of the Metal–Ligand Interaction. The Journal of Physical Chemistry A. 120(48). 9529–9544. 11 indexed citations
10.

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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