Danielle Gully

28 papers receiving 1.6k citations

Peers

Danielle Gully
Comparison fields: 5 of 84
  • Cellular and Molecular Neuroscience 1.2k
  • Behavioral Neuroscience 197
  • Biological Psychiatry 89
  • Reproductive Medicine 201
  • Endocrine and Autonomic Systems 143
Replace Adair J. Hotchkiss with:
Adair J. Hotchkiss United States
K J Chang United States
Hideki Hiyama Japan
Ali Ardati Switzerland
John A. Morrow United Kingdom
Deborra Mullins United States
Juan M. Luque Spain
Jean‐René Cardinaux Switzerland
Y. Torrens France
V. Daugé France
Danielle Gully relative to Adair J. Hotchkiss United States Adair J. Hotchkiss's profile →
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Citations per year

Countries citing papers authored by Danielle Gully

Since Specialization
Citations

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

Fields of papers citing papers by Danielle Gully

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1998333
2 2002197
3 1997181
4 199996
5 199871
6 199967
7 199465
8 199365
9 199761
10 199760
11 199657
12 199955
13 199748
14 199846
15 199737
16 199736
17 199432
18 199531
19 199425
20 199423

About Danielle Gully

Danielle Gully is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology, Oncology, Physiology and Reproductive Medicine, having authored 28 papers that have together received 1.7k indexed citations. Recurring topics across this work include Neuropeptides and Animal Physiology (25 papers), Receptor Mechanisms and Signaling (21 papers), Peptidase Inhibition and Analysis (6 papers), Hypothalamic control of reproductive hormones (4 papers), Pain Mechanisms and Treatments (3 papers), Chemical Synthesis and Analysis (3 papers), Stress Responses and Cortisol (2 papers) and Signaling Pathways in Disease (2 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (1.2k citations), Behavioral Neuroscience (197 citations), Biological Psychiatry (89 citations), Reproductive Medicine (201 citations) and Endocrine and Autonomic Systems (143 citations). Danielle Gully has collaborated with scholars based in France, Germany and United States. Frequent co-authors include Jean‐Pierre Maffrand, Natalio Vita, Jean Mazella, Joëlle Chabry, Jean‐Pierre Vincent, R. Steinberg, Philippe Soubrié, Mourad Kaghad, Valérie Navarro and Pascual Ferrara. Their work appears in journals such as European Journal of Pharmacology, Journal of Biological Chemistry, Journal of Pharmacology and Experimental Therapeutics, Neuroendocrinology and Cancer.

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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