Akinori Eiyama

841 citations
8 papers · 651 · 1 hit paper · h-index 7

Impact in

Papers in

    • Mitochondrial Function and Pathology 4
    • Ubiquitin and proteasome pathways 2
    • Signaling Pathways in Disease 1
    • ATP Synthase and ATPases Research 1
    • Autophagy in Disease and Therapy 5

Akinori Eiyama

8 papers receiving 641 citations

Akinori Eiyama's Hit Papers

PINK1/Parkin-mediated mitophagy in mammalian cells 2015 · 469 citations
4690+3+7Years since publication100200300400

Peers

Akinori Eiyama
Comparison fields: 5 of 85
  • Geriatrics and Gerontology 40
  • Epidemiology 346
  • Neurology 98
  • Cell Biology 104
  • Clinical Biochemistry 43
Replace Haixia Zhuang with:
Haixia Zhuang China
Ioanna Daskalaki Greece
Christina Ploumi Greece
Salwa Sebti United States
Esmaa Bouhamida Italy
Yujun Shen China
Guadalupe Martínez-Chacón Spain
You-Jin Lee South Korea
Haoran Tai China
Julie Faitg United Kingdom
Akinori Eiyama relative to Haixia Zhuang China Haixia Zhuang's profile →
Citations per field
00.5×1.5×2.4×
Haixia Zhuang · 1×
Citations per year

Countries citing papers authored by Akinori Eiyama

Since Specialization
Citations

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

Fields of papers citing papers by Akinori Eiyama

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

8 of 8 papers shown
#Work
1
PINK1/Parkin-mediated mitophagy in mammalian cells
Hit paper breakdown →
2015469
2 201350
3 201245
4 201536
5 201530
6 202110
7 201710
8 20221

About Akinori Eiyama

Akinori Eiyama is a scholar working on Molecular Biology, Epidemiology, Neurology, Cell Biology and Oncology, having authored 8 papers that have together received 651 indexed citations. Recurring topics across this work include Autophagy in Disease and Therapy (5 papers), Mitochondrial Function and Pathology (4 papers), Parkinson's Disease Mechanisms and Treatments (3 papers), Ubiquitin and proteasome pathways (2 papers), Peptidase Inhibition and Analysis (1 paper), Signaling Pathways in Disease (1 paper), Erythrocyte Function and Pathophysiology (1 paper) and ATP Synthase and ATPases Research (1 paper). The work is most often cited by research in Geriatrics and Gerontology (40 citations), Epidemiology (346 citations), Neurology (98 citations), Cell Biology (104 citations) and Clinical Biochemistry (43 citations). Akinori Eiyama has collaborated with scholars based in Japan, Germany and United Kingdom. Frequent co-authors include Koji Okamoto, Noriko Kondo‐Okamoto, Kenji Suzuki, Takahiro Ueba, Yoji Kawano, Fugo Takasu, Shin Ishii, Honda Naoki, Aiko Okada and Takako Kaneko‐Kawano. Their work appears in journals such as Journal of Biological Chemistry, Current Opinion in Cell Biology, The EMBO Journal, Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics and FEBS Letters.

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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