Hideki Yagi

4.5k citations
137 papers · 2.5k indexed · h-index 28
Topics
Immune Cell Function and Interaction (15 papers)T-cell and B-cell Immunology (13 papers)Growth Hormone and Insulin-like Growth Factors (9 papers)

In The Last Decade

Hideki Yagi

134 papers receiving 2.5k citations

Peers

Hideki Yagi
Comparison fields: 5 of 128
  • Molecular Biology 848
  • Immunology 799
  • Surgery 443
  • Endocrinology, Diabetes and Metabolism 351
  • Genetics 348
Replace Gaetano Calı̀ with:
Gaetano Calı̀ Italy
Shin‐ichi Harashima Japan
T Kishimoto Japan
Victorine Douin‐Echinard France
Paula M. Oliver United States
Allan Sirsjö Sweden
Rainer Meyer Germany
Nicholas Obermüller Germany
Baohui Xu United States
Robert W. McMurray United States
Hideki Yagi relative to Gaetano Calı̀ Italy Gaetano Calı̀'s profile →
Citations per field
00.5×1.6×
Gaetano Calı̀ · 1×
Citations per year

Countries citing papers authored by Hideki Yagi

Since Specialization
Citations

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

Fields of papers citing papers by Hideki Yagi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hideki Yagi

This figure shows the co-authorship network connecting the top 25 collaborators of Hideki Yagi. A scholar is included among the top collaborators of Hideki Yagi 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 Hideki Yagi. Hideki Yagi 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
#WorkIndexed citations
1 1
2 4
3 10
4 182
5 6
6 27
7
Gene Transfer of the High Mobility Group Box 1 Inhibitor in Rat Acute Liver Failure Model
1
8 29
9 8
10 0
11
PJ-633 Alcohol produces imbalance of adrenal and neuronal sympathtic activity in patients with alcohol-induced NMS(Autonomic Nervous System 5 (H) : PJ106)(Poster Session (Japanese))
1
12 77
13 8
14 23
15 7
16 24
17 1
18 2
19 0
20 3

About Hideki Yagi

Hideki Yagi is a scholar working on Applied Microbiology and Biotechnology, Immunology and Endocrinology, Diabetes and Metabolism, having authored 137 papers that have together received 2.5k indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (15 papers), T-cell and B-cell Immunology (13 papers) and Growth Hormone and Insulin-like Growth Factors (9 papers). The work is most often cited by research in Immunology (799 citations), Endocrinology, Diabetes and Metabolism (351 citations) and Genetics (348 citations). Hideki Yagi has collaborated with scholars based in Japan, United States and Belgium. Frequent co-authors include Yoshiyuki Hashimoto, Masanori Nakamura, Takashi Nishimura, Tsunetoshi Itoh, Minoru Harada, Yasushi Uchiyama, Mitsunobu Matsumoto, Takemi Enomoto, Masayuki Seki and Hiroyuki Soga. Their work appears in journals such as Proceedings of the National Academy of Sciences, The Journal of Experimental Medicine and The Journal of Immunology.

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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