G. Gon

455 citations
11 papers · 412 indexed · h-index 9

Impact in

Papers in

G. Gon

11 papers receiving 409 citations

Peers

G. Gon
Comparison fields: 5 of 58
  • Reproductive Medicine 117
  • Cellular and Molecular Neuroscience 241
  • Endocrinology, Diabetes and Metabolism 150
  • Behavioral Neuroscience 31
  • Endocrine and Autonomic Systems 58
Replace Marie A. Tavianini with:
Marie A. Tavianini United States
Valérie Turquier France
Miguel Ángel Vargas Mexico
Amanda D. Taylor United Kingdom
C.J.C. Boersma Netherlands
B D Weintraub United States
W. C. Dermody United States
Kirti Chaturvedi United States
M.C. Woussen-Colle Belgium
Philippe De Neef Belgium
G. Gon relative to Marie A. Tavianini United States Marie A. Tavianini's profile →
Citations per field
00.5×
Marie A. Tavianini · 1×
Citations per year

Countries citing papers authored by G. Gon

Since Specialization
Citations

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

Fields of papers citing papers by G. Gon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

11 of 11 papers shown
#Work
1 199653
2 199213
3 19911
4 199047
5 199075
6 198980
7 198989
8 19885
9 198712
10 198713
11 198724

About G. Gon

G. Gon is a scholar working on Behavioral Neuroscience, Cellular and Molecular Neuroscience, Neurology, Endocrinology, Diabetes and Metabolism and Reproductive Medicine, having authored 11 papers that have together received 412 indexed citations. Recurring topics across this work include Neuropeptides and Animal Physiology (4 papers), Pituitary Gland Disorders and Treatments (3 papers), Barrier Structure and Function Studies (2 papers), Hypothalamic control of reproductive hormones (2 papers), Genetic and Kidney Cyst Diseases (2 papers), Growth Hormone and Insulin-like Growth Factors (2 papers), Receptor Mechanisms and Signaling (2 papers) and Stress Responses and Cortisol (1 paper). The work is most often cited by research in Reproductive Medicine (117 citations), Cellular and Molecular Neuroscience (241 citations), Endocrinology, Diabetes and Metabolism (150 citations), Behavioral Neuroscience (31 citations) and Endocrine and Autonomic Systems (58 citations). G. Gon has collaborated with scholars based in Japan, United Kingdom and United States. Frequent co-authors include Stephen R. Bloom, Jennifer H. Steel, Philip Jones, Domhnall O’Halloran, J. M. Polak, Mohammad A. Ghatei, Hiroshi Ishikawa, Adel Giaid, Julia M. Polak and Hiroshi Ishikawa. Their work appears in journals such as Endocrinology, Cell and Tissue Research, Regulatory Peptides, The Anatomical Record and Journal of Leukocyte Biology.

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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