Tomohide Masuda

1.6k citations
12 papers · 886 · 1 hit paper · h-index 7

Impact in

Papers in

Tomohide Masuda

12 papers receiving 864 citations

Tomohide Masuda's Hit Papers

GNINA 1.0: molecular docking with deep learning 2021 · 438 citations
4380+1+3Years since publication100200300400

Peers

Tomohide Masuda
Comparison fields: 5 of 110
  • Computational Theory and Mathematics 486
  • Molecular Biology 519
  • Materials Chemistry 244
  • Pharmacology 66
  • Animal Science and Zoology 43
Replace Jeffrey Wagner with:
Jeffrey Wagner United States
Florian Flachsenberg Germany
Eva Nittinger Germany
Woong‐Hee Shin South Korea
John W. Mayfield United States
Kunqian Yu China
Mark A. Hermsmeier United States
Maykel Cruz‐Monteagudo Portugal
Wenhua Kuang China
Agnes Meyder Germany
Tomohide Masuda relative to Jeffrey Wagner United States Jeffrey Wagner's profile →
Citations per field
00.5×2.5×
Jeffrey Wagner · 1×
Citations per year

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-authors

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

All Works

12 of 12 papers shown
#Work
1
GNINA 1.0: molecular docking with deep learning
Hit paper breakdown →
2021438
2 2020192
3 2022122
4 201666
5 202031
6 201416
7 201611
8
Morphometric and Histopathological Evaluation of a Probiotic and its Synergism with Vaccination against Coccidiosis in Broilers
20146
9 20251
10 20241
11 20251
12 20201

About Tomohide Masuda

Tomohide Masuda is a scholar working on Materials Chemistry, Molecular Biology, Computational Theory and Mathematics, Organic Chemistry and Small Animals, having authored 12 papers that have together received 886 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (5 papers), Protein Structure and Dynamics (3 papers), Machine Learning in Materials Science (3 papers), Animal Nutrition and Physiology (2 papers), Lanthanide and Transition Metal Complexes (2 papers), Click Chemistry and Applications (1 paper), Organometallic Complex Synthesis and Catalysis (1 paper) and SARS-CoV-2 detection and testing (1 paper). The work is most often cited by research in Computational Theory and Mathematics (486 citations), Molecular Biology (519 citations), Materials Chemistry (244 citations), Pharmacology (66 citations) and Animal Science and Zoology (43 citations). Tomohide Masuda has collaborated with scholars based in Japan, United States and India. Frequent co-authors include David Ryan Koes, Matthew Ragoza, Jocelyn Sunseri, Paul Francoeur, Andrew T. McNutt, Rishal Aggarwal, Rocco Meli, I. M. Snyder, Takamitsu Tsukahara and Daisuke Kurosawa. Their work appears in journals such as Journal of Chemical Information and Modeling, The Journal of Physical Chemistry A, Animal Science Journal, Scientific Reports and Chemistry Letters.

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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