Masashi Mori

6.6k citations
100 papers · 4.9k indexed · 1 hit paper · h-index 38

Masashi Mori

97 papers receiving 4.7k citations

Hit Papers

Real-world COVID-19 vaccine effectiveness against the Omi...1162023202620242025255075100

Peers

Masashi Mori
Comparison fields: 5 of 126
  • Endocrinology 450
  • Molecular Medicine 388
  • Biotechnology 668
  • Plant Science 2.5k
  • Molecular Biology 2.6k
Replace Vittorio Venturi with:
Vittorio Venturi Italy
Azat Badretdin United States
Ian K. Toth United Kingdom
Nancy H. C. Roosens Belgium
Jean‐Yves Coppée France
Stephen K. Farrand United States
Aaron A. Klammer United States
Gregory T. Robertson United States
Yi‐Hu Dong Singapore
Alan Collmer United States
Masashi Mori relative to Vittorio Venturi Italy Vittorio Venturi's profile →
Citations per field
00.5×1.5×
Vittorio Venturi · 1×
Citations per year

Countries citing papers authored by Masashi Mori

Since Specialization
Citations

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

Fields of papers citing papers by Masashi Mori

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1
Real-world COVID-19 vaccine effectiveness against the Omicron BA.2 variant in a SARS-CoV-2 infection-naive populationbreakdown →
2023116
2 20233
3 202313
4 202217
5 202114
6 202110
7 2018140
8 201832
9 201521
10 20144
11 2013106
12 201119
13 201048
14 200986
15 20083
16 2007150
17 200133
18 19946
19 199313
20 19893

About Masashi Mori

Masashi Mori is a scholar working on Endocrinology, Biotechnology and Molecular Medicine, having authored 100 papers that have together received 4.9k indexed citations. Recurring topics across this work include Plant Virus Research Studies (18 papers), Transgenic Plants and Applications (14 papers), Plant-Microbe Interactions and Immunity (13 papers), Bacterial Genetics and Biotechnology (12 papers), Bacteriophages and microbial interactions (10 papers), Plant Molecular Biology Research (10 papers), Antibiotic Resistance in Bacteria (9 papers) and Plant Reproductive Biology (7 papers). The work is most often cited by research in Endocrinology (450 citations), Molecular Medicine (388 citations) and Biotechnology (668 citations). Masashi Mori has collaborated with scholars based in Japan, United States and Australia. Frequent co-authors include Norio Agata, M Ohta, Koji Dohi, Minoru Isobe, Michio Ohta, Ikuko Hara‐Nishimura, Atsushi Tamai, Hironori Koga, Tomoo Shimada and Shinya Ohki. Their work appears in journals such as Nature, Science and Proceedings of the National Academy of Sciences.

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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