Daisuke Sato

3.2k citations
64 papers · 2.4k · h-index 25

Impact in

Papers in

Daisuke Sato

60 papers receiving 2.4k citations

Peers

Daisuke Sato
Comparison fields: 5 of 102
  • Cardiology and Cardiovascular Medicine 1.9k
  • Cellular and Molecular Neuroscience 519
  • Molecular Biology 1.5k
  • Statistical and Nonlinear Physics 235
  • Electrochemistry 71
Replace Kenneth R. Laurita with:
Kenneth R. Laurita United States
Lai‐Hua Xie United States
Leighton T. Izu United States
Eric A. Sobie United States
M. Saleet Jafri United States
Ronald Wilders Netherlands
Joseph L. Greenstein United States
J. Andrew Wasserstrom United States
Penelope A. Boyden United States
I. Kodama Japan
Daisuke Sato relative to Kenneth R. Laurita United States Kenneth R. Laurita's profile →
Citations per field
00.5×1.5×2.5×
Kenneth R. Laurita · 1×
Citations per year

Countries citing papers authored by Daisuke Sato

Since Specialization
Citations

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

Fields of papers citing papers by Daisuke Sato

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 64 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007305
2 2010253
3 2009205
4 2006138
5 2005132
6 2009118
7 200688
8 200878
9 201076
10 200772
11 201357
12 201854
13 201149
14 200948
15 201548
16 201147
17 201344
18 201742
19 201936
20 201933

About Daisuke Sato

Daisuke Sato is a scholar working on Cardiology and Cardiovascular Medicine, Molecular Biology, Cellular and Molecular Neuroscience, Statistical and Nonlinear Physics and Computer Networks and Communications, having authored 64 papers that have together received 2.4k indexed citations. Recurring topics across this work include Cardiac electrophysiology and arrhythmias (50 papers), Ion channel regulation and function (38 papers), Neuroscience and Neural Engineering (14 papers), stochastic dynamics and bifurcation (6 papers), ECG Monitoring and Analysis (5 papers), Neuroscience and Neuropharmacology Research (4 papers), Porphyrin Metabolism and Disorders (4 papers) and Receptor Mechanisms and Signaling (4 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (1.9k citations), Cellular and Molecular Neuroscience (519 citations), Molecular Biology (1.5k citations), Statistical and Nonlinear Physics (235 citations) and Electrochemistry (71 citations). Daisuke Sato has collaborated with scholars based in United States, Japan and Norway. Frequent co-authors include James N. Weiss, Zhilin Qu, Alan Garfinkel, Yohannes Shiferaw, Donald M. Bers, Yuanfang Xie, Alain Karma, Lai‐Hua Xie, Peng‐Sheng Chen and Riccardo Olcese. Their work appears in journals such as Biophysical Journal, The Journal of Physiology, Biochemistry, The Journal of General Physiology and Heliyon.

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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