Akiko Furuya
- Virology top 5%
- Molecular Biology top 5%
- Glycosylation and Glycoproteins Research 8
- RNA Research and Splicing 4
- Nephrology top 5%
- Immunology top 5%
- Cancer Research top 10%
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- Diabetes Management and Research 9
- Hyperglycemia and glycemic control in critically ill and hospitalized patients 9
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- Monoclonal and Polyclonal Antibodies Research 7
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- Pancreatic function and diabetes 5
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- Diabetes and associated disorders 4
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- Caveolin-1 and cellular processes 3
- Co-authors
- Nobuo HanaiTadashi WadaHiroshi HandaYuki YamaguchiKeiichi YanoSeiji SugimotoJun HasegawaToshiyuki Takagi
- Cited by
- VirologyMolecular BiologyNephrology
- Partner nations
- JapanUnited StatesSingapore
In The Last Decade
Akiko Furuya
65 papers receiving 3.0k citations
Hit Papers
Peers
Comparison fields: 5 of 111
- Virology 133
- Molecular Biology 1.9k
- Nephrology 180
- Immunology 460
- Cancer Research 247
Countries citing papers authored by Akiko Furuya
This map shows the geographic impact of Akiko Furuya'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 Akiko Furuya with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Akiko Furuya more than expected).
Fields of papers citing papers by Akiko Furuya
This network shows the impact of papers produced by Akiko Furuya. 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 Akiko Furuya. The network helps show where Akiko Furuya may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Akiko Furuya, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 8 | |
| 2 | 2020 | 1 | |
| 3 | 2016 | 37 | |
| 4 | 2014 | 5 | |
| 5 | 2013 | 14 | |
| 6 | 2012 | 21 | |
| 7 | The Role of N-Terminal Pro-B-Type Natriuretic Peptide in the Diagnosis of Congestive Heart Failure in Children: Correlation With the Heart Failure Score and Comparison With B-Type Natriuretic Peptide (小児のうっ血性心不全診断におけるN-末端Pro-B型Na利尿ペプチドの役割 心不全評点との相関及びB型Na利尿ペプチドとの比較) | 2010 | 5 |
| 8 | 2010 | 49 | |
| 9 | 2009 | 69 | |
| 10 | 2005 | 200 | |
| 11 | 2004 | 102 | |
| 12 | 2004 | 94 | |
| 13 | 2003 | 59 | |
| 14 | 2003 | 106 | |
| 15 | 2003 | 21 | |
| 16 | 2000 | 36 | |
| 17 | 2000 | 73 | |
| 18 | 1998 | 106 | |
| 19 | 1994 | 85 | |
| 20 | 1990 | 79 |
About Akiko Furuya
Akiko Furuya is a scholar working on Endocrinology, Diabetes and Metabolism, Immunology and Allergy and Physiology, having authored 65 papers that have together received 3.0k indexed citations. Recurring topics across this work include Diabetes Management and Research (9 papers), Hyperglycemia and glycemic control in critically ill and hospitalized patients (9 papers), Glycosylation and Glycoproteins Research (8 papers), Monoclonal and Polyclonal Antibodies Research (7 papers), Pancreatic function and diabetes (5 papers), Diabetes and associated disorders (4 papers), RNA Research and Splicing (4 papers) and Caveolin-1 and cellular processes (3 papers). The work is most often cited by research in Virology (133 citations), Molecular Biology (1.9k citations) and Nephrology (180 citations). Akiko Furuya has collaborated with scholars based in Japan, United States and Singapore. Frequent co-authors include Nobuo Hanai, Tadashi Wada, Hiroshi Handa, Yuki Yamaguchi, Keiichi Yano, Seiji Sugimoto, Jun Hasegawa, Toshiyuki Takagi, Toshihiko Fujimori and Yo‐ichi Nabeshima. Their work appears in journals such as Science, Cell and Journal of Biological Chemistry.
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.