Masaaki Kagimoto

1.2k citations
24 papers · 963 indexed · h-index 13

Masaaki Kagimoto

22 papers receiving 934 citations

Peers

Masaaki Kagimoto
Comparison fields: 5 of 80
  • Pharmacology 328
  • Endocrinology, Diabetes and Metabolism 392
  • Clinical Biochemistry 87
  • Molecular Biology 566
  • Genetics 228
Replace J Picado-Leonard with:
J Picado-Leonard United States
E Małunowicz Poland
Jacob G. Ghazarian United States
Sarah Chouinard Canada
Tatsuya Ogishima Japan
Yoshikazu Emi Japan
Maria Celeste Lechner Portugal
Alexandra G. Ianculescu United States
Ivaylo Stoilov United States
Jeffrey D. Kearbey United States
Masaaki Kagimoto relative to J Picado-Leonard United States J Picado-Leonard's profile →
Citations per field
00.5×1.7×
J Picado-Leonard · 1×
Citations per year

Countries citing papers authored by Masaaki Kagimoto

Since Specialization
Citations

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

Fields of papers citing papers by Masaaki Kagimoto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 199611
2 199241
3 199220
4 19905
5 1990215
6 198936
7 1989126
8 198932
9 198978
10 198816
11 1988122
12 19889
13 198727
14
Identification of abnormal hemoglobin (J Lome): beta 59 (E3) lysine----asparagine in a Japanese.
19860
15
Thalassemia in Japan.
19854
16 19856
17 198411
18 198428
19 19844
20 19835

About Masaaki Kagimoto

Masaaki Kagimoto is a scholar working on Clinical Biochemistry, Endocrinology, Diabetes and Metabolism, Genetics, Biochemistry and Molecular Biology, having authored 24 papers that have together received 963 indexed citations. Recurring topics across this work include Sexual Differentiation and Disorders (8 papers), Metabolism and Genetic Disorders (4 papers), Hormonal and reproductive studies (3 papers), Hemoglobinopathies and Related Disorders (3 papers), Glycosylation and Glycoproteins Research (2 papers), Amino Acid Enzymes and Metabolism (2 papers), Mitochondrial Function and Pathology (2 papers) and Epigenetics and DNA Methylation (2 papers). The work is most often cited by research in Pharmacology (328 citations), Endocrinology, Diabetes and Metabolism (392 citations), Clinical Biochemistry (87 citations), Molecular Biology (566 citations) and Genetics (228 citations). Masaaki Kagimoto has collaborated with scholars based in United States, Japan and Canada. Frequent co-authors include Michael R. Waterman, Tanja Zeugin, Markus H. Heim, Urs Meyer, E R Simpson, Jeremy S.D. Winter, Evan R. Simpson, John McCarthy, Matthew C. Lorence and J. Ian Mason. Their work appears in journals such as Journal of Biological Chemistry, Human Genetics, Molecular Endocrinology, Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease and Archives of Biochemistry and Biophysics.

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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