Junta Doi

61 total papers · 475 total citations
37 papers, 393 citations indexed

About

Junta Doi is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition and Computational Mechanics. According to data from OpenAlex, Junta Doi has authored 37 papers receiving a total of 393 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 10 papers in Computer Vision and Pattern Recognition and 9 papers in Computational Mechanics. Recurrent topics in Junta Doi's work include 3D Surveying and Cultural Heritage (9 papers), Protein Structure and Dynamics (8 papers) and Robotics and Sensor-Based Localization (7 papers). Junta Doi is often cited by papers focused on 3D Surveying and Cultural Heritage (9 papers), Protein Structure and Dynamics (8 papers) and Robotics and Sensor-Based Localization (7 papers). Junta Doi collaborates with scholars based in Japan, France and Canada. Junta Doi's co-authors include Mitsunori Ikeguchi, Hidetoshi Kono, Shugo Nakamura, Wataru Sato, Takeshi Kawabata, Makoto Nishiyama, Masaru Tanokura, Hitoshi Hirose, Kentaro Shimizu and Masakazu Sekijima and has published in prestigious journals such as Nucleic Acids Research, The Journal of Chemical Physics and The Journal of Physical Chemistry.

In The Last Decade

Junta Doi

36 papers receiving 380 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Junta Doi 233 117 72 46 40 37 393
Ding Lu 80 0.3× 103 0.9× 17 0.2× 15 0.3× 20 0.5× 25 335
Hongzhi Li 48 0.2× 123 1.1× 150 2.1× 31 0.7× 13 0.3× 28 441
Marcin Kowiel 190 0.8× 129 1.1× 55 0.8× 23 0.5× 6 0.1× 26 374
K. J. Harrison 46 0.2× 163 1.4× 19 0.3× 15 0.3× 18 0.5× 41 434
John W. Arthur 23 0.1× 105 0.9× 116 1.6× 16 0.3× 31 0.8× 28 386
Madhumita Panda 64 0.3× 25 0.2× 38 0.5× 95 2.1× 31 0.8× 34 414
Christoph Niedermeier 89 0.4× 22 0.2× 90 1.3× 19 0.4× 8 0.2× 25 382
David Allouche 224 1.0× 68 0.6× 71 1.0× 6 0.1× 5 0.1× 17 380
Yukito Iba 157 0.7× 91 0.8× 56 0.8× 18 0.4× 6 0.1× 24 374
Changyu Hu 59 0.3× 55 0.5× 103 1.4× 16 0.3× 17 0.4× 42 446

Countries citing papers authored by Junta Doi

Since Specialization
Citations

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

Fields of papers citing papers by Junta Doi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Junta Doi

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

All Works

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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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