Naoki Kimura

999 citations
30 papers · 771 · h-index 13

Impact in

Papers in

Naoki Kimura

26 papers receiving 720 citations

Peers

Naoki Kimura
Comparison fields: 5 of 80
  • Developmental Neuroscience 104
  • Computational Theory and Mathematics 139
  • Algebra and Number Theory 34
  • Organic Chemistry 209
  • Inorganic Chemistry 79
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Christina Esdar Germany
Svetlana Belyanskaya United States
Hongguang Pan United States
Shafiq U. Ahmed United Kingdom
Nathalie Desban France
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Citations per field
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Citations per year

Countries citing papers authored by Naoki Kimura

Since Specialization
Citations

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

Fields of papers citing papers by Naoki Kimura

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1999278
2 201779
3 195867
4 195863
5 199550
6 202133
7 200832
8 201326
9 201923
10
T lymphoid/myeloid bilineal crisis in chronic myelogenous leukemia.
199323
11 201817
12 197816
13
Immunogenotypes and clonal culture analysis in B-precursor acute lymphoblastic leukemia.
199213
14
Immunoglobulin and T cell receptor gene rearrangements in Philadelphia chromosome-positive leukemia: a different involvement pattern in blast crisis and acute leukemia.
19909
15 20048
16 19588
17 20087
18 19545
19 20213
20 20203

About Naoki Kimura

Naoki Kimura is a scholar working on Computational Theory and Mathematics, Organic Chemistry, Management Science and Operations Research, Rheumatology and Immunology, having authored 30 papers that have together received 771 indexed citations. Recurring topics across this work include semigroups and automata theory (9 papers), Catalytic C–H Functionalization Methods (6 papers), Fuzzy and Soft Set Theory (5 papers), Cyclopropane Reaction Mechanisms (3 papers), Advanced Algebra and Logic (3 papers), Synthesis and Catalytic Reactions (3 papers), Asymmetric Hydrogenation and Catalysis (2 papers) and Chronic Myeloid Leukemia Treatments (2 papers). The work is most often cited by research in Developmental Neuroscience (104 citations), Computational Theory and Mathematics (139 citations), Algebra and Number Theory (34 citations), Organic Chemistry (209 citations) and Inorganic Chemistry (79 citations). Naoki Kimura has collaborated with scholars based in Japan, United States and Netherlands. Frequent co-authors include Fumitoshi Kakiuchi, Takuya Kochi, Makoto Yanagisawa, Tadamitsu Kishimoto, Hirokazu Arakawa, Tatsuhiro Hisatsune, Kinichi Nakashima, Stefan Wiese, Tetsuya Taga and Kanji Yoshida. Their work appears in journals such as Semigroup Forum, Asian Journal of Organic Chemistry, Journal of the American Chemical Society, Synthesis and Biochemical and Biophysical Research Communications.

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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