Kristian Gundersen

65 papers receiving 4.6k citations

Kristian Gundersen's Hit Papers

Three myosin heavy chain isoforms in type 2 skeletal muscle fibres 1989 · 832 citations
8320+12+24Years since publication250500750

Peers

Kristian Gundersen
Comparison fields: 5 of 134
  • Aging 129
  • Rehabilitation 424
  • Cell Biology 822
  • Molecular Biology 3.3k
  • Physiology 1.1k
Replace Kenneth M. Baldwin with:
Kenneth M. Baldwin United States
Simon M. Hughes United Kingdom
Tejvir S. Khurana United States
K. M. Baldwin United States
Mario Molinaro Italy
Kenneth S. Campbell United States
Robert J. Talmadge United States
Geoffrey Goldspink United Kingdom
Gerta Vrbovà United Kingdom
A. Wernig Germany
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Citations per field
00.5×2.7×
Kenneth M. Baldwin · 1×
Citations per year

Countries citing papers authored by Kristian Gundersen

Since Specialization
Citations

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

Fields of papers citing papers by Kristian Gundersen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 66 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Three myosin heavy chain isoforms in type 2 skeletal muscle fibres
Hit paper breakdown →
1989832
2 2003332
3 2010234
4 1990205
5 2003193
6 2010191
7 1999162
8 2016147
9 2008129
10 1998126
11 1988120
12 2006111
13 2016111
14 2008109
15 1988102
16 2013101
17 198898
18 201281
19 199879
20 198877

About Kristian Gundersen

Kristian Gundersen is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Physiology, Cardiology and Cardiovascular Medicine and Biomedical Engineering, having authored 66 papers that have together received 4.7k indexed citations. Recurring topics across this work include Muscle Physiology and Disorders (44 papers), Cardiomyopathy and Myosin Studies (11 papers), Adipose Tissue and Metabolism (11 papers), Muscle activation and electromyography studies (10 papers), Nuclear Structure and Function (8 papers), Genetic Neurodegenerative Diseases (7 papers), RNA Research and Splicing (5 papers) and Cardiovascular Effects of Exercise (5 papers). The work is most often cited by research in Aging (129 citations), Rehabilitation (424 citations), Cell Biology (822 citations), Molecular Biology (3.3k citations) and Physiology (1.1k citations). Kristian Gundersen has collaborated with scholars based in Norway, United States and Italy. Frequent co-authors include Jo C. Bruusgaard, Terje Lømo, Stefano Schiaffino, Luisa Gorza, Simonetta Ausoni, Ingrid M. Egner, Zaheer A. Rana, Leopoldo Saggin, Saverio Sartore and Göran Nilsson. Their work appears in journals such as The Journal of Physiology, Muscle & Nerve, Proceedings of the National Academy of Sciences, Acta Physiologica and Journal of Applied Physiology.

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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