Daniel Béchet

84 papers receiving 3.8k citations

Peers

Daniel Béchet
Comparison fields: 5 of 122
  • Cell Biology 1.1k
  • Rehabilitation 358
  • Physiology 1.0k
  • Aging 61
  • Molecular Biology 2.3k
Replace Daniel Taillandier with:
Daniel Taillandier France
Ruben Mestril United States
Jarrod A. Call United States
Mitsunori Miyazaki Japan
Henri Bernardi France
M. Richard Sayen United States
Dawit A. P. Gonçalves Brazil
Joseph D. Etlinger United States
Paulo R. Jannig Sweden
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Daniel Béchet relative to Daniel Taillandier France Daniel Taillandier's profile →
Citations per field
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Citations per year

Countries citing papers authored by Daniel Béchet

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Béchet

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 89 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1996229
2 2005200
3 2000175
4 2005174
5 2005155
6 2001146
7 2005141
8 2006128
9 2008125
10 2005121
11 2011121
12 2014115
13 2001105
14 201380
15 201474
16 199074
17 200871
18 200468
19 201464
20 200460

About Daniel Béchet

Daniel Béchet is a scholar working on Cell Biology, Molecular Biology, Physiology, Rehabilitation and Epidemiology, having authored 89 papers that have together received 3.8k indexed citations. Recurring topics across this work include Muscle Physiology and Disorders (38 papers), Muscle metabolism and nutrition (17 papers), Ubiquitin and proteasome pathways (13 papers), Adipose Tissue and Metabolism (13 papers), Calpain Protease Function and Regulation (7 papers), Autophagy in Disease and Therapy (7 papers), Exercise and Physiological Responses (6 papers) and Genetic Neurodegenerative Diseases (6 papers). The work is most often cited by research in Cell Biology (1.1k citations), Rehabilitation (358 citations), Physiology (1.0k citations), Aging (61 citations) and Molecular Biology (2.3k citations). Daniel Béchet has collaborated with scholars based in France, Italy and United States. Frequent co-authors include Didier Attaix, Lydie Combaret, Daniel Taillandier, Christiane Deval, Marc Ferrara, Sylvie B. Mordier, Anne Listrat, Amina Tassa, Sophie Ventadour and Audrey Codran. Their work appears in journals such as Journal of Cachexia Sarcopenia and Muscle, The International Journal of Biochemistry & Cell Biology, International Journal of Molecular Sciences, Biochemical Journal and American Journal of Physiology-Endocrinology and Metabolism.

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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