Masaki Hikida

97 total papers · 4.1k total citations
75 papers, 3.5k citations indexed

About

Masaki Hikida is a scholar working on Immunology, Molecular Biology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Masaki Hikida has authored 75 papers receiving a total of 3.5k indexed citations (citations by other indexed papers that have themselves been cited), including 48 papers in Immunology, 23 papers in Molecular Biology and 19 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Masaki Hikida's work include T-cell and B-cell Immunology (42 papers), Immune Cell Function and Interaction (31 papers) and Monoclonal and Polyclonal Antibodies Research (18 papers). Masaki Hikida is often cited by papers focused on T-cell and B-cell Immunology (42 papers), Immune Cell Function and Interaction (31 papers) and Monoclonal and Polyclonal Antibodies Research (18 papers). Masaki Hikida collaborates with scholars based in Japan, United States and France. Masaki Hikida's co-authors include Tomohiro Kurosaki, Hitoshi Ohmori, Yoko Fujii, Yoshihiro Baba, Yasuo Mori, Toshiyuki Takai, Toshio Hirano, Keigo Nishida, Yukio Ando and Masahiro Kitano and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

In The Last Decade

Masaki Hikida

73 papers receiving 3.5k citations

Author Peers

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

Author Last Decade Papers Cites
Masaki Hikida 2.0k 1.2k 525 328 275 75 3.5k
Yoshihiro Baba 1.8k 0.9× 1.5k 1.3× 1.0k 1.9× 313 1.0× 240 0.9× 87 4.1k
Zhangguo Chen 1.2k 0.6× 1.2k 1.0× 540 1.0× 571 1.7× 303 1.1× 52 2.9k
Yoshiteru Sasaki 2.2k 1.1× 1.9k 1.6× 303 0.6× 825 2.5× 151 0.5× 49 4.1k
David G. Motto 2.1k 1.1× 1.4k 1.2× 83 0.2× 367 1.1× 218 0.8× 58 3.9k
Roy K. Cheung 1.0k 0.5× 942 0.8× 110 0.2× 509 1.6× 160 0.6× 62 2.8k
Georges Bismuth 3.4k 1.7× 2.2k 1.9× 173 0.3× 1.3k 3.9× 333 1.2× 132 6.1k
Eugenio Monti 750 0.4× 2.3k 2.0× 154 0.3× 159 0.5× 167 0.6× 112 3.2k
I. Caroline Le Poole 2.0k 1.0× 886 0.8× 340 0.6× 414 1.3× 52 0.2× 101 4.1k
Wolfgang W. Schamel 3.5k 1.8× 2.3k 2.0× 172 0.3× 1.6k 4.7× 764 2.8× 141 6.2k
Naomi J. Logsdon 930 0.5× 1.2k 1.0× 87 0.2× 461 1.4× 118 0.4× 40 3.0k

Countries citing papers authored by Masaki Hikida

Since Specialization
Citations

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

Fields of papers citing papers by Masaki Hikida

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Masaki Hikida

This figure shows the co-authorship network connecting the top 25 collaborators of Masaki Hikida. A scholar is included among the top collaborators of Masaki Hikida 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 Masaki Hikida. Masaki Hikida 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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