Michael Nivala

1.1k citations
21 papers · 807 · h-index 15

Impact in

Papers in

Michael Nivala

21 papers receiving 792 citations

Peers

Michael Nivala
Comparison fields: 5 of 79
  • Cardiology and Cardiovascular Medicine 557
  • Statistical and Nonlinear Physics 170
  • Cellular and Molecular Neuroscience 147
  • Mathematical Physics 67
  • Molecular Biology 435
Replace J.L. Stephenson with:
J.L. Stephenson United States
Rüdiger Thul United Kingdom
Anthony Varghese United States
Yohannes Shiferaw United States
Elizabeth J. Akin United States
Vladimir E. Bondarenko United States
J. W. Stucki Switzerland
James Eason United States
J. Mailen Kootsey United States
Philip R. Ershler United States
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Citations per field
00.5×5×12.3×
J.L. Stephenson · 1×
Citations per year

Countries citing papers authored by Michael Nivala

Since Specialization
Citations

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

Fields of papers citing papers by Michael Nivala

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 21 scholars most cited alongside Michael Nivala, 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 Michael Nivala Line = papers co-authored together Michael Nivala links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011140
2 201593
3 201578
4 201264
5 201261
6 201250
7 201447
8 201243
9 201643
10 201138
11 200531
12 201030
13 201128
14 201325
15 201016
16 20097
17 20156
18 20132
19 20112
20 20152

About Michael Nivala

Michael Nivala is a scholar working on Cardiology and Cardiovascular Medicine, Molecular Biology, Statistical and Nonlinear Physics, Cellular and Molecular Neuroscience and Mathematical Physics, having authored 21 papers that have together received 807 indexed citations. Recurring topics across this work include Cardiac electrophysiology and arrhythmias (12 papers), Ion channel regulation and function (9 papers), Nonlinear Waves and Solitons (5 papers), Nonlinear Photonic Systems (3 papers), Neuroscience and Neural Engineering (3 papers), Protein Structure and Dynamics (3 papers), Advanced Mathematical Physics Problems (3 papers) and Nonlinear Dynamics and Pattern Formation (2 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (557 citations), Statistical and Nonlinear Physics (170 citations), Cellular and Molecular Neuroscience (147 citations), Mathematical Physics (67 citations) and Molecular Biology (435 citations). Michael Nivala has collaborated with scholars based in United States and New Zealand. Frequent co-authors include Zhilin Qu, James N. Weiss, Bernard Deconinck, Christopher Y. Ko, Zhen Song, Alan Garfinkel, Michael B. Liu, Enno de Lange, Neha Singh and Arash Pezhouman. Their work appears in journals such as Biophysical Journal, Journal of Molecular and Cellular Cardiology, Studies in Applied Mathematics, Circulation and Journal of Physics A Mathematical and Theoretical.

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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