F. Cadepond

14 papers receiving 875 citations

Peers

F. Cadepond
Comparison fields: 5 of 86
  • Behavioral Neuroscience 66
  • Endocrinology, Diabetes and Metabolism 239
  • Genetics 360
  • Reproductive Medicine 64
  • Immunology 155
Replace T. Kawashima with:
T. Kawashima Japan
Friedrich C. Dalman United States
A. Bailly France
Lawrence C. Scherrer United States
Kurt D. Dittmar United States
Yvonne A. Lefebvre Canada
Maria-Grazia Catelli France
H. Loosfelt France
Bonnie A. Maler United States
J A Wells United States
F. Cadepond relative to T. Kawashima Japan T. Kawashima's profile →
Citations per field
00.5×9.5×
T. Kawashima · 1×
Citations per year

Countries citing papers authored by F. Cadepond

Since Specialization
Citations

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

Fields of papers citing papers by F. Cadepond

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

14 of 14 papers shown
#Work
1 1997347
2 1988214
3 1991134
4 1994108
5 199329
6 199419
7 199211
8 200210
9 19859
10 19909
11
Redox mechanism for the chaperone activity of heat shock proteins HSPs 60, 70 and 90 as suggested by hydrophobic cluster analysis: hypothesis.
19945
12 19994
13 19922
14
Are receptor-associated nuclear proteins associated with the earliest effects of steroid hormones?
19901

About F. Cadepond

F. Cadepond is a scholar working on Molecular Biology, Immunology, Endocrinology, Diabetes and Metabolism, Genetics and Reproductive Medicine, having authored 14 papers that have together received 902 indexed citations. Recurring topics across this work include Heat shock proteins research (7 papers), Estrogen and related hormone effects (5 papers), Hormonal Regulation and Hypertension (4 papers), Toxin Mechanisms and Immunotoxins (3 papers), Hypothalamic control of reproductive hormones (2 papers), Enzyme Structure and Function (2 papers), Viral Infectious Diseases and Gene Expression in Insects (1 paper) and NF-κB Signaling Pathways (1 paper). The work is most often cited by research in Behavioral Neuroscience (66 citations), Endocrinology, Diabetes and Metabolism (239 citations), Genetics (360 citations), Reproductive Medicine (64 citations) and Immunology (155 citations). F. Cadepond has collaborated with scholars based in France and Belgium. Frequent co-authors include E.E. Baulieu, A Ulmann, Ghislaine Schweizer-Groyer, E.E. Baulieu, Nicole Jibard, M.G. Catelli, Vincent Giguère, Ronald M. Evans, William B. Pratt and Anne Guiochon‐Mantel. Their work appears in journals such as The Journal of Steroid Biochemistry and Molecular Biology, Journal of Biological Chemistry, Annals of the New York Academy of Sciences, Proceedings of the National Academy of Sciences and Annual Review of Medicine.

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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