Akihiro Muto

1.8k citations
36 papers · 1.5k · h-index 20

Impact in

  • Hematology top 5%
    • Acute Myeloid Leukemia Research
  • Immunology top 10%
    • Immune Response and Inflammation

Papers in

    • Retinoids in leukemia and cellular processes 13
    • Advanced biosensing and bioanalysis techniques 4
    • Natural product bioactivities and synthesis 3
    • Acute Myeloid Leukemia Research 12

Akihiro Muto

36 papers receiving 1.5k citations

Peers

Akihiro Muto
Comparison fields: 5 of 104
  • Hematology 230
  • Immunology 411
  • Toxicology 49
  • Cancer Research 206
  • Biochemistry 77
Replace Daeho Cho with:
Daeho Cho South Korea
Rebecca Chinery United Kingdom
Françoise Besançon France
Sekhar Majumdar India
C Kunsch United States
Haoqiang Wan China
Hiroshi Azuma Japan
Tomoyuki Tanaka Japan
Hyun‐Mee Oh South Korea
Mutsuhiko Minami Japan
Akihiro Muto relative to Daeho Cho South Korea Daeho Cho's profile →
Citations per field
00.5×4.5×
Daeho Cho · 1×
Citations per year

Countries citing papers authored by Akihiro Muto

Since Specialization
Citations

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

Fields of papers citing papers by Akihiro Muto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2001436
2 2007106
3 199695
4 201080
5 201678
6 201470
7 199966
8 201860
9 199657
10 200050
11 200745
12 199639
13 200737
14 200235
15 200134
16 199633
17 201222
18 199822
19 199720
20 201520

About Akihiro Muto

Akihiro Muto is a scholar working on Molecular Biology, Hematology, Oncology, Genetics and Cancer Research, having authored 36 papers that have together received 1.5k indexed citations. Recurring topics across this work include Retinoids in leukemia and cellular processes (13 papers), Acute Myeloid Leukemia Research (12 papers), Estrogen and related hormone effects (7 papers), Cancer-related Molecular Pathways (5 papers), Advanced biosensing and bioanalysis techniques (4 papers), Natural product bioactivities and synthesis (3 papers), Sarcoma Diagnosis and Treatment (3 papers) and Natural Compounds in Disease Treatment (2 papers). The work is most often cited by research in Hematology (230 citations), Immunology (411 citations), Toxicology (49 citations), Cancer Research (206 citations) and Biochemistry (77 citations). Akihiro Muto has collaborated with scholars based in Japan, United States and Egypt. Frequent co-authors include Naohiro Inohara, Gabriel Núñez, Felicia F. Chen, Yasunori Ogura, Masahiro Kizaki, Yasuo Ikeda, Hironori Ueno, Hiromichi Matsushita, Yumi Fukuchi and Takatsune Shimizu. Their work appears in journals such as Blood, Leukemia Research, Journal of Biological Chemistry, Molecular Cancer Therapeutics and British Journal of Cancer.

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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