Naoki Mori

7.3k citations
338 papers · 5.1k indexed · h-index 39

Naoki Mori

310 papers receiving 4.9k citations

Peers

Naoki Mori
Comparison fields: 5 of 164
  • Insect Science 1.4k
  • Plant Science 2.7k
  • Ecology, Evolution, Behavior and Systematics 766
  • Genetics 788
  • Molecular Biology 1.3k
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Jia Ye China
Beverley J. Glover United Kingdom
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Citations per field
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Citations per year

Countries citing papers authored by Naoki Mori

Since Specialization
Citations

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

Fields of papers citing papers by Naoki Mori

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20250
3 20240
4 20230
5 20222
6 202135
7 20215
8 20201
9 20206
10 202027
11 201531
12
A Study of Driver Workload Estimation by the VACP Method
20150
13
Post-germination seedling vigor under submergence and submergence-induced SUB1A gene expression in indica and japonica rice (Oryza sativa L.)
201015
14
Differential cDNA-AFLP screening of transcripts associated with brown planthopper resistance in rice ( Oryza sativa L.)
20093
15 20081
16
Constructing linkage maps of brown planthopper resistance genes Bph1, bph2, and Bph9 on rice chromosome 12.
20032
17
Organophosphate resistance in grape leafhoppers and IPM strategies.
20014
18
Research and Analysis of energy consumption in office buildings
20000
19
The entropy evaluation method for the thermodynamical selection rule
19994
20 19904

About Naoki Mori

Naoki Mori is a scholar working on Insect Science, Plant Science and Ecology, Evolution, Behavior and Systematics, having authored 338 papers that have together received 5.1k indexed citations. Recurring topics across this work include Insect-Plant Interactions and Control (72 papers), Insect and Pesticide Research (47 papers), Wheat and Barley Genetics and Pathology (38 papers), Study of Mite Species (32 papers), Ultrasonics and Acoustic Wave Propagation (23 papers), Plant Disease Resistance and Genetics (20 papers), Evolutionary Algorithms and Applications (18 papers) and Metaheuristic Optimization Algorithms Research (18 papers). The work is most often cited by research in Insect Science (1.4k citations), Plant Science (2.7k citations) and Ecology, Evolution, Behavior and Systematics (766 citations). Naoki Mori has collaborated with scholars based in Japan, United States and Philippines. Frequent co-authors include Chiharu Nakamura, Yasumasa KUWAHARA, Ritsuo Nishida, Shigeo Takumi, Naoko Yoshinaga, Takashige Ishii, Shiro Biwa, K. Tsunewaki, James H. Tumlinson and Hans T. Alborn. Their work appears in journals such as Bioscience Biotechnology and Biochemistry, Journal of Chemical Ecology, Genes & Genetic Systems, Theoretical and Applied Genetics and Ultrasonics.

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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