Daniel E. Michele

6.3k citations
74 papers · 5.2k · h-index 35

Impact in

Papers in

Daniel E. Michele

73 papers receiving 5.1k citations

Peers

Daniel E. Michele
Comparison fields: 5 of 111
  • Immunology and Allergy 330
  • Molecular Biology 3.8k
  • Cardiology and Cardiovascular Medicine 1.2k
  • Rehabilitation 315
  • Cell Biology 796
Replace Rita Barresi with:
Rita Barresi United Kingdom
Yoshihide Sunada Japan
Silvia Torelli United Kingdom
Beril Talim Türkiye
Yuko Miyagoe‐Suzuki Japan
Paul T. Martin United States
Eijiro Ozawa Japan
Patrizia Sabatelli Italy
Melissa J. Spencer United States
Reginald E. Bittner Austria
Daniel E. Michele relative to Rita Barresi United Kingdom Rita Barresi's profile →
Citations per field
00.5×1.5×
Rita Barresi · 1×
Citations per year

Countries citing papers authored by Daniel E. Michele

Since Specialization
Citations

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

Fields of papers citing papers by Daniel E. Michele

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel E. Michele. 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 Daniel E. Michele. The network helps show where Daniel E. Michele may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 74 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2002685
2 2002485
3 2003354
4 2005270
5 2002245
6 2004223
7 2004221
8 2011201
9 1999153
10 2006148
11 2009129
12 2011123
13 201189
14 200882
15 200182
16 199979
17 200478
18 199977
19 200673
20 201473

About Daniel E. Michele

Daniel E. Michele is a scholar working on Cardiology and Cardiovascular Medicine, Molecular Biology, Rehabilitation, Cell Biology and Cellular and Molecular Neuroscience, having authored 74 papers that have together received 5.2k indexed citations. Recurring topics across this work include Muscle Physiology and Disorders (43 papers), Cardiomyopathy and Myosin Studies (20 papers), Cardiovascular Effects of Exercise (11 papers), Exercise and Physiological Responses (10 papers), Viral Infections and Immunology Research (6 papers), Adipose Tissue and Metabolism (6 papers), Genetic Neurodegenerative Diseases (6 papers) and Cellular Mechanics and Interactions (4 papers). The work is most often cited by research in Immunology and Allergy (330 citations), Molecular Biology (3.8k citations), Cardiology and Cardiovascular Medicine (1.2k citations), Rehabilitation (315 citations) and Cell Biology (796 citations). Daniel E. Michele has collaborated with scholars based in United States, France and Japan. Frequent co-authors include Kevin P. Campbell, Joseph M. Metzger, Steven A. Moore, Fumiaki Saito, Rita Barresi, Ronald D. Cohn, Motoi Kanagawa, Faris P. Albayya, Ichizo Nishino and Jakob S. Satz. Their work appears in journals such as American Journal of Physiology-Heart and Circulatory Physiology, Proceedings of the National Academy of Sciences, Nature, The FASEB Journal and American Journal of Physiology-Cell 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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