Go Kito

1.0k citations
51 papers · 798 · h-index 15

Impact in

    • Pharmacogenetics and Drug Metabolism
    • Drug-Induced Hepatotoxicity and Protection
    • Inflammatory mediators and NSAID effects
  • Neurology top 10%
    • Neuroinflammation and Neurodegeneration Mechanisms

Papers in

Go Kito

48 papers receiving 782 citations

Peers

Go Kito
Comparison fields: 5 of 96
  • Pharmacology 244
  • Neurology 74
  • Biochemistry 63
  • Endocrine and Autonomic Systems 45
  • Oncology 179
Replace Bangning Yu with:
Bangning Yu United States
Weina Zhu China
P. Vecsei Germany
Uffe Bang Olsen Denmark
Rosanna Tamborra Italy
Adaline C. Smith United States
C D Malis United States
Helmuth Sippel Finland
Alison D. McNeilly United Kingdom
Zhihong Lin China
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Citations per field
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Bangning Yu · 1×
Citations per year

Countries citing papers authored by Go Kito

Since Specialization
Citations

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

Fields of papers citing papers by Go Kito

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 51 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006108
2 200183
3 200764
4 200955
5 200138
6 200837
7 200834
8 200633
9 198930
10 198126
11 197024
12 201622
13 200222
14 198416
15 199514
16 200613
17
Neural mechanism for production of spasmodic expiratory response like cough induced by amygdala stimulation in the cat. I. Pathways from the amygdala to the lower brain stem.
197713
18 198912
19 199410
20 200610

About Go Kito

Go Kito is a scholar working on Molecular Biology, Cardiology and Cardiovascular Medicine, Pharmacology, Organic Chemistry and Pulmonary and Respiratory Medicine, having authored 51 papers that have together received 798 indexed citations. Recurring topics across this work include Pharmacogenetics and Drug Metabolism (7 papers), Respiratory and Cough-Related Research (5 papers), Neuroscience of respiration and sleep (5 papers), Receptor Mechanisms and Signaling (4 papers), Acute Ischemic Stroke Management (4 papers), Cardiac electrophysiology and arrhythmias (3 papers), Plant-based Medicinal Research (3 papers) and Neuroscience and Neuropharmacology Research (3 papers). The work is most often cited by research in Pharmacology (244 citations), Neurology (74 citations), Biochemistry (63 citations), Endocrine and Autonomic Systems (45 citations) and Oncology (179 citations). Go Kito has collaborated with scholars based in Japan, France and Switzerland. Frequent co-authors include Ryoichi Nagata, Yasuhiro Uno, Tetsuya Kamataki, Hideki Fujino, Teruo Susumu, Yuji Kuge, Kazuo Minematsu, Chiaki Yokota, Akira Nishimura and Y Kasé. Their work appears in journals such as Drug Metabolism and Disposition, Hypertension Research, Journal of Pharmacological Sciences, Journal of Cerebral Blood Flow & Metabolism and Life Sciences.

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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