Kevin M. Barnes

6.7k citations
98 papers · 5.0k indexed · h-index 43

Kevin M. Barnes

98 papers receiving 4.8k citations

Peers

Kevin M. Barnes
Comparison fields: 5 of 155
  • Reproductive Medicine 1.3k
  • Endocrinology, Diabetes and Metabolism 1.9k
  • Genetics 1.3k
  • Rheumatology 547
  • Behavioral Neuroscience 124
Replace Ora Hirsch Pescovitz with:
Ora Hirsch Pescovitz United States
Margaret E. Wierman United States
Tomonobu Hasegawa Japan
M. Jansen Netherlands
Jock K. Findlay Australia
Guy Van Vliet Canada
Erica A. Eugster United States
Olaf Hiort Germany
Ana Cláudia Latronico Brazil
Jörg Gromoll Germany
Kevin M. Barnes relative to Ora Hirsch Pescovitz United States Ora Hirsch Pescovitz's profile →
Citations per field
00.5×1.5×2.1×
Ora Hirsch Pescovitz · 1×
Citations per year

Countries citing papers authored by Kevin M. Barnes

Since Specialization
Citations

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

Fields of papers citing papers by Kevin M. Barnes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kevin M. Barnes. 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 Kevin M. Barnes. The network helps show where Kevin M. Barnes may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20237
2 20207
3 20135
4 201130
5 200795
6 2007100
7 200743
8 200657
9 20033
10 2001149
11 200023
12 200050
13 1999101
14 199836
15 199613
16 19933
17 199115
18 198914
19 198740
20 198537

About Kevin M. Barnes

Kevin M. Barnes is a scholar working on Reproductive Medicine, Endocrinology, Diabetes and Metabolism and Behavioral Neuroscience, having authored 98 papers that have together received 5.0k indexed citations. Recurring topics across this work include Growth Hormone and Insulin-like Growth Factors (32 papers), Hypothalamic control of reproductive hormones (27 papers), Sexual Differentiation and Disorders (24 papers), Hormonal and reproductive studies (8 papers), Epigenetics and DNA Methylation (8 papers), Osteoarthritis Treatment and Mechanisms (8 papers), Ovarian function and disorders (7 papers) and TGF-β signaling in diseases (7 papers). The work is most often cited by research in Reproductive Medicine (1.3k citations), Endocrinology, Diabetes and Metabolism (1.9k citations) and Genetics (1.3k citations). Kevin M. Barnes has collaborated with scholars based in United States, Hungary and Cameroon. Frequent co-authors include Gordon B. Cutler, Jeffrey Baron, Susan R. Rose, Ola Nilsson, Ora Hirsch Pescovitz, Mercedes Uriarte, Martina Weise, Rachel I. Gafni, Karen Hench and Verónica Abad. Their work appears in journals such as New England Journal of Medicine, Proceedings of the National Academy of Sciences and Nature Communications.

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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