Daichi Inoue

3.3k citations
55 papers · 864 indexed · h-index 16

Impact in

  • Hematology top 2%
    • Acute Myeloid Leukemia Research
  • Genetics top 5%
    • Myeloproliferative Neoplasms: Diagnosis and Treatment

Papers in

    • Acute Myeloid Leukemia Research 19
    • Myeloproliferative Neoplasms: Diagnosis and Treatment 10

Daichi Inoue

51 papers receiving 857 citations

Peers

Daichi Inoue
Comparison fields: 5 of 70
  • Hematology 482
  • Genetics 212
  • Molecular Biology 473
  • Cancer Research 84
  • Immunology 115
Replace Matteo Da Vià with:
Matteo Da Vià Italy
Lisa Pleyer Austria
Takeki Mitsui Japan
T. Karakas Germany
Bruce Petersen United States
Mineo Kurokawa Japan
Anna Jankowska United States
Barbara Crescenzi Italy
Junyuan Qi China
Klaus Fenchel Germany
Daichi Inoue relative to Matteo Da Vià Italy Matteo Da Vià's profile →
Citations per field
00.5×1.5×2.5×
Matteo Da Vià · 1×
Citations per year

Countries citing papers authored by Daichi Inoue

Since Specialization
Citations

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

Fields of papers citing papers by Daichi Inoue

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20252
3 20250
4 20243
5 20242
6 20236
7 20234
8 202214
9 20201
10 20192
11 201885
12 201746
13 201678
14 20146
15 201332
16 20125
17 20126
18 201110
19 201020
20 20096

About Daichi Inoue

Daichi Inoue is a scholar working on Hematology, Genetics, Immunology, Molecular Biology and Rheumatology, having authored 55 papers that have together received 864 indexed citations. Recurring topics across this work include Acute Myeloid Leukemia Research (19 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (10 papers), RNA Research and Splicing (7 papers), Protein Degradation and Inhibitors (6 papers), Ubiquitin and proteasome pathways (5 papers), RNA modifications and cancer (5 papers), Viral-associated cancers and disorders (4 papers) and Epigenetics and DNA Methylation (4 papers). The work is most often cited by research in Hematology (482 citations), Genetics (212 citations), Molecular Biology (473 citations), Cancer Research (84 citations) and Immunology (115 citations). Daichi Inoue has collaborated with scholars based in Japan, United States and Taiwan. Frequent co-authors include Omar Abdel‐Wahab, Toshio Kitamura, Robert K. Bradley, Reina Nagase, Makoto Saika, Takayuki Takahashi, Takeshi Fujino, Sumie Tabata, Akiko Matsushita and Kimihito C. Kawabata. Their work appears in journals such as International Journal of Hematology, Experimental Hematology, Blood, Acta Haematologica and Scientific Reports.

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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