Shigemi Kimura

2.0k citations
36 papers · 1.7k · h-index 16

Impact in

  • Genetics top 5%
    • Mesenchymal stem cell research
    • Virus-based gene therapy research
    • Muscle Physiology and Disorders
    • Pluripotent Stem Cells Research

Papers in

Shigemi Kimura

35 papers receiving 1.6k citations

Peers

Shigemi Kimura
Comparison fields: 5 of 54
  • Genetics 125
  • Molecular Biology 603
  • Physiology 249
  • Rheumatology 58
  • Urology 14
Replace Paloma Martínez‐Redondo with:
Paloma Martínez‐Redondo Spain
Chiara Rinaldi Italy
Baohong Cao United States
Diana J. Watt United Kingdom
Javiera B Bravo-Alegria United States
Dalia Waldman Israel
Jessica C. Tebbets United States
Juan A. García‐Porrero Spain
Ana Volarevic Serbia
Toshihiro Inubushi Japan
Shigemi Kimura relative to Paloma Martínez‐Redondo Spain Paloma Martínez‐Redondo's profile →
Citations per field
00.5×2×4×6.6×
Paloma Martínez‐Redondo · 1×
Citations per year

Countries citing papers authored by Shigemi Kimura

Since Specialization
Citations

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

Fields of papers citing papers by Shigemi Kimura

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Shigemi Kimura, 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 Shigemi Kimura Line = papers co-authored together Shigemi Kimura 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 2000535
2 2009252
3 2003203
4 2017107
5 199398
6 200654
7 201448
8 201744
9 201537
10 201429
11 200727
12 201126
13 200325
14 200425
15 201421
16 199720
17 200715
18 202113
19 199811
20 200610

About Shigemi Kimura

Shigemi Kimura is a scholar working on Molecular Biology, Endocrine and Autonomic Systems, Infectious Diseases, Physiology and Neurology, having authored 36 papers that have together received 1.7k indexed citations. Recurring topics across this work include Muscle Physiology and Disorders (17 papers), Lysosomal Storage Disorders Research (3 papers), SARS-CoV-2 and COVID-19 Research (3 papers), Pluripotent Stem Cells Research (2 papers), Circadian rhythm and melatonin (2 papers), Animal Genetics and Reproduction (2 papers), Sleep and related disorders (1 paper) and Autoimmune Neurological Disorders and Treatments (1 paper). The work is most often cited by research in Genetics (125 citations), Molecular Biology (603 citations), Physiology (249 citations), Rheumatology (58 citations) and Urology (14 citations). Shigemi Kimura has collaborated with scholars based in Japan, United States and Germany. Frequent co-authors include Baohong Cao, Johnny Huard, Zhuqing Qu‐Petersen, James H. Cummins, Paul D. Robbins, Charley Gates, Joon Yung Lee, Anton Wernig, Arvydas Ūsas and Makoto Ikezawa. Their work appears in journals such as Neuromuscular Disorders, Brain and Development, Scientific Reports, Journal of Child Neurology and Development Growth & Differentiation.

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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