Naohiro Yano

2.4k total citations
86 papers, 1.8k citations indexed

About

Naohiro Yano is a scholar working on Molecular Biology, Nephrology and Genetics. According to data from OpenAlex, Naohiro Yano has authored 86 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Molecular Biology, 25 papers in Nephrology and 15 papers in Genetics. Recurrent topics in Naohiro Yano's work include Renal Diseases and Glomerulopathies (23 papers), Adipose Tissue and Metabolism (8 papers) and Diabetes and associated disorders (7 papers). Naohiro Yano is often cited by papers focused on Renal Diseases and Glomerulopathies (23 papers), Adipose Tissue and Metabolism (8 papers) and Diabetes and associated disorders (7 papers). Naohiro Yano collaborates with scholars based in United States, Japan and China. Naohiro Yano's co-authors include Yi‐Tang Tseng, Ting C. Zhao, James F. Padbury, Masayuki Endoh, Shougang Zhuang, Gangjian Qin, Yasuo Nomoto, Ting C. Zhao, Richard G. Moore and Hideto Sakai and has published in prestigious journals such as Journal of Biological Chemistry, SHILAP Revista de lepidopterología and The Journal of Immunology.

In The Last Decade

Naohiro Yano

84 papers receiving 1.8k citations

Peers

Naohiro Yano
Comparison fields: 5 of 113
  • Molecular Biology 819
  • Physiology 408
  • Cardiology and Cardiovascular Medicine 278
  • Nephrology 242
  • Immunology 217
Replace Nicholas R. Ferreri with:
Nicholas R. Ferreri United States
Denis Féliers United States
Christophe Montessuit Switzerland
Howard Goldberg Canada
Kenji Kasuno Japan
Linda Davis United States
Giulio R. Romeo United States
Jun Shi China
Clara E. Magyar United States
Joëlle Perez France
Nicholas R. Ferreri United States View profile →
Citations per field, relative to Naohiro Yano
Naohiro Yano · 1×
Citations per year, relative to Naohiro Yano
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Countries citing papers authored by Naohiro Yano

Since Specialization
Citations

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

Fields of papers citing papers by Naohiro Yano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Naohiro Yano

This figure shows the co-authorship network connecting the top 25 collaborators of Naohiro Yano. A scholar is included among the top collaborators of Naohiro Yano based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Naohiro Yano. Naohiro Yano is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 1
2 15
3 9
4 6
5 22
6 21
7 19
8 5
9 19
10 116
11 49
12 28
13 95
14 38
15 11
16
Clustering gene expression data using self-organizing maps and k-means clustering
10
17 25
18 31
19 22
20 11

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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