John N. Stallone

2.4k citations
64 papers · 2.0k · h-index 27

Impact in

Papers in

John N. Stallone

62 papers receiving 2.0k citations

Peers

John N. Stallone
Comparison fields: 5 of 98
  • Endocrinology, Diabetes and Metabolism 821
  • Behavioral Neuroscience 67
  • Physiology 425
  • Genetics 419
  • Endocrine and Autonomic Systems 94
Replace Marinella Rosselli with:
Marinella Rosselli Switzerland
P. C. Bates United Kingdom
Janice D. Wagner United States
Suzanne G. Laychock United States
J. D. M. Albano United Kingdom
Mercedes Perusquı́a Mexico
Yan‐Yun Liu United States
Jean Grizard France
Fumihiko Sasaki Japan
N. Altszuler United States
John N. Stallone relative to Marinella Rosselli Switzerland Marinella Rosselli's profile →
Citations per field
00.5×1.5×2.3×
Marinella Rosselli · 1×
Citations per year

Countries citing papers authored by John N. Stallone

Since Specialization
Citations

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

Fields of papers citing papers by John N. Stallone

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John N. Stallone. 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 John N. Stallone. The network helps show where John N. Stallone may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 64 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2001181
2 1996133
3 2003127
4 2001103
5 201184
6 201083
7 199776
8 200871
9 199169
10 200762
11 200958
12 201453
13 201146
14 198646
15 201346
16 198643
17 200841
18 199339
19 198538
20 199238

About John N. Stallone

John N. Stallone is a scholar working on Endocrinology, Diabetes and Metabolism, Physiology, Genetics, Molecular Biology and Social Psychology, having authored 64 papers that have together received 2.0k indexed citations. Recurring topics across this work include Nitric Oxide and Endothelin Effects (19 papers), Hormonal and reproductive studies (14 papers), Estrogen and related hormone effects (13 papers), Neuroendocrine regulation and behavior (12 papers), Receptor Mechanisms and Signaling (12 papers), Hormonal Regulation and Hypertension (12 papers), Menopause: Health Impacts and Treatments (10 papers) and Pharmacological Effects and Assays (6 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (821 citations), Behavioral Neuroscience (67 citations), Physiology (425 citations), Genetics (419 citations) and Endocrine and Autonomic Systems (94 citations). John N. Stallone has collaborated with scholars based in United States, Mexico and China. Frequent co-authors include Mercedes Perusquı́a, E. J. Braun, Richard E. White, Viju P. Deenadayalu, Xuan Yu, Guichun Han, Alfredo J. Garcia, Xumei Gao, Gregory W. Rutecki and Frederick C. Whittier. Their work appears in journals such as American Journal of Physiology-Heart and Circulatory Physiology, The FASEB Journal, American Journal of Physiology-Regulatory, Integrative and Comparative Physiology, PLoS ONE and Biology of Sex Differences.

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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