Miki Uesaka

415 citations
11 papers · 296 · h-index 9

Impact in

Papers in

    • Genomics and Chromatin Dynamics 3
    • Epigenetics and DNA Methylation 2
    • Genomics and Phylogenetic Studies 2
    • RNA and protein synthesis mechanisms 1
    • Hippo pathway signaling and YAP/TAZ 2

Miki Uesaka

10 papers receiving 294 citations

Peers

Miki Uesaka
Comparison fields: 5 of 44
  • Physiology 23
  • Endocrinology, Diabetes and Metabolism 50
  • Genetics 78
  • Reproductive Medicine 21
  • Cell Biology 36
Replace Yinglun Sheng with:
Yinglun Sheng Canada
Guohui Shang China
Jingjing L. Kipp United States
Marı́a Elena Torres-Padilla France
Gustavo Zamberlam Canada
Vishal Khivansara United States
Wei Xiang China
Stacey McGee United States
Wenke Wang China
Nai-Chi Hsu Taiwan
Miki Uesaka relative to Yinglun Sheng Canada Yinglun Sheng's profile →
Citations per field
00.5×6.3×
Yinglun Sheng · 1×
Citations per year

Countries citing papers authored by Miki Uesaka

Since Specialization
Citations

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

Fields of papers citing papers by Miki Uesaka

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

11 of 11 papers shown
#Work
1 200781
2 201660
3 201642
4 200735
5 200617
6 201017
7 202214
8 201812
9 200810
10 20228
11 20260

About Miki Uesaka

Miki Uesaka is a scholar working on Molecular Biology, Cell Biology, Genetics, Cellular and Molecular Neuroscience and Rheumatology, having authored 11 papers that have together received 296 indexed citations. Recurring topics across this work include Genomics and Chromatin Dynamics (3 papers), Genetic and Clinical Aspects of Sex Determination and Chromosomal Abnormalities (2 papers), Epigenetics and DNA Methylation (2 papers), Genomics and Phylogenetic Studies (2 papers), Hippo pathway signaling and YAP/TAZ (2 papers), RNA and protein synthesis mechanisms (1 paper), Hormonal and reproductive studies (1 paper) and Chromosomal and Genetic Variations (1 paper). The work is most often cited by research in Physiology (23 citations), Endocrinology, Diabetes and Metabolism (50 citations), Genetics (78 citations), Reproductive Medicine (21 citations) and Cell Biology (36 citations). Miki Uesaka has collaborated with scholars based in Japan, United States and Russia. Frequent co-authors include Kaoru Miyamoto, Tetsuya Mizutani, Takashi Yazawa, Shinji Honda, Eric U. Selker, Andrew D. Klocko, Jonathan M. Galazka, Michael Freitag, Akihiro Umezawa and Takashi Kajitani. Their work appears in journals such as Reproductive Biology and Endocrinology, Genetics, Endocrinology, Journal of Biological Chemistry and Frontiers in Endocrinology.

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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