Makoto Kanno

868 citations
44 papers · 662 indexed · h-index 12

Makoto Kanno

40 papers receiving 634 citations

Peers

Makoto Kanno
Comparison fields: 5 of 110
  • Nephrology 123
  • Clinical Biochemistry 58
  • Oncology 140
  • Toxicology 16
  • Ophthalmology 40
Replace Yoshihiro Hiramatsu with:
Yoshihiro Hiramatsu Japan
Hideyuki Watanabe Japan
A Ando Japan
Glenn V. Dalrymple United States
Lorenzo Franceschini Italy
Marta Martin‐Lorenzo Spain
Kei Takano Japan
B. G. Blijenberg Netherlands
Xiaoguang Shao China
Himanshu Gupta United States
Makoto Kanno relative to Yoshihiro Hiramatsu Japan Yoshihiro Hiramatsu's profile →
Citations per field
00.5×4.7×
Yoshihiro Hiramatsu · 1×
Citations per year

Countries citing papers authored by Makoto Kanno

Since Specialization
Citations

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

Fields of papers citing papers by Makoto Kanno

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 202134
2 202119
3 201911
4 20196
5 20170
6 20176
7 201340
8 20133
9 20134
10 201130
11 20102
12 201015
13 20021
14 200211
15
Apoptotic index correlates to bcl-2 and p53 protein expression, histological grade and prognosis in invasive breast cancers.
199876
16
Role of neutrophils in lipid peroxidation at reperfusion in liver transplantation.
19963
17 19887
18 19861
19
Non-linearity measuring method using two frequencies to electrical components
19850
20 19645

About Makoto Kanno

Makoto Kanno is a scholar working on Nephrology, Bioengineering and Computer Networks and Communications, having authored 44 papers that have together received 662 indexed citations. Recurring topics across this work include Sensor Technology and Measurement Systems (10 papers), Advanced Electrical Measurement Techniques (7 papers), Dialysis and Renal Disease Management (6 papers), Force Microscopy Techniques and Applications (3 papers), Electrical Contact Performance and Analysis (3 papers), Chronic Kidney Disease and Diabetes (3 papers), Cancer-related Molecular Pathways (3 papers) and Analytical Chemistry and Sensors (3 papers). The work is most often cited by research in Nephrology (123 citations), Clinical Biochemistry (58 citations) and Oncology (140 citations). Makoto Kanno has collaborated with scholars based in Japan, Australia and Indonesia. Frequent co-authors include Atsuo Tsuchiya, Izo Kimijima, Tsuyoshi Watanabe, Koichi Asahi, Hiroshi Kimura, R Abe, Kenichi Tanaka, Hiroki Sato, Seiichi Takenoshita and Toru Watanabe. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

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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