Makoto Terada

46 total papers · 1.2k total citations
35 papers, 983 citations indexed

About

Makoto Terada is a scholar working on Molecular Biology, Neurology and Rheumatology. According to data from OpenAlex, Makoto Terada has authored 35 papers receiving a total of 983 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 6 papers in Neurology and 6 papers in Rheumatology. Recurrent topics in Makoto Terada's work include Parkinson's Disease Mechanisms and Treatments (4 papers), IgG4-Related and Inflammatory Diseases (2 papers) and Aldose Reductase and Taurine (2 papers). Makoto Terada is often cited by papers focused on Parkinson's Disease Mechanisms and Treatments (4 papers), IgG4-Related and Inflammatory Diseases (2 papers) and Aldose Reductase and Taurine (2 papers). Makoto Terada collaborates with scholars based in Japan, United States and France. Makoto Terada's co-authors include Yoshiki Nishizawà, Shuzo Otani, H Morii, Akira Tamaoka, Minoru Inaba, Masato Hasegawa, Takashi Nonaka, Tadayoshi Hasuma, Yoshihisa Yano and Hidenori Koyama and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Blood.

In The Last Decade

Makoto Terada

31 papers receiving 970 citations

Author Peers

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

Author						Papers	Cites
Makoto Terada	279	155	131	130	121	35	983
T Ishida	241 0.9×	91 0.6×	33 0.3×	26 0.2×	78 0.6×	51	818
Yuki Yokota	290 1.0×	58 0.4×	49 0.4×	108 0.8×	123 1.0×	54	1.1k
S. Vukelic	227 0.8×	65 0.4×	39 0.3×	28 0.2×	57 0.5×	36	1.0k
Akiko Miyazaki	251 0.9×	80 0.5×	49 0.4×	118 0.9×	106 0.9×	43	845
Wenzhi Chen	158 0.6×	50 0.3×	110 0.8×	40 0.3×	49 0.4×	63	1.1k
Katharina Maier	258 0.9×	76 0.5×	123 0.9×	10 0.1×	122 1.0×	26	1.2k
Jiajie Li	430 1.5×	81 0.5×	26 0.2×	41 0.3×	96 0.8×	62	968
Clive R. Hamlin	333 1.2×	137 0.9×	105 0.8×	54 0.4×	49 0.4×	30	1.0k
Eimear Dunne	387 1.4×	38 0.2×	51 0.4×	31 0.2×	117 1.0×	43	1.2k
Akira Kawata	326 1.2×	58 0.4×	21 0.2×	41 0.3×	262 2.2×	34	979

Countries citing papers authored by Makoto Terada

Since Specialization

Citations

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

Fields of papers citing papers by Makoto Terada

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Makoto Terada

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