Danielle M. Gerhard

2.0k citations
25 papers · 1.4k · h-index 16

Impact in

Papers in

Danielle M. Gerhard

24 papers receiving 1.4k citations

Peers

Danielle M. Gerhard
Comparison fields: 5 of 87
  • Biological Psychiatry 549
  • Behavioral Neuroscience 258
  • Cellular and Molecular Neuroscience 593
  • Pharmacology 506
  • Developmental Neuroscience 68
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Lace M. Riggs United States
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Indira Mendez‐David France
Plínio Casarotto Finland
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Kenichi Fukumoto Japan
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Citations per field
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Citations per year

Countries citing papers authored by Danielle M. Gerhard

Since Specialization
Citations

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

Fields of papers citing papers by Danielle M. Gerhard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019258
2 2016239
3 2020155
4 2016122
5 2016118
6 201974
7 202069
8 201647
9 201839
10
Rapid-Acting Antidepressants: Mechanistic Insights and Future Directions.
201837
11 202036
12 201435
13 201834
14 201423
15 202019
16 202019
17
Neuroscience. 5th Edition
201311
18 20239
19 20219
20 20229

About Danielle M. Gerhard

Danielle M. Gerhard is a scholar working on Pharmacology, Cellular and Molecular Neuroscience, Biological Psychiatry, Behavioral Neuroscience and Social Psychology, having authored 25 papers that have together received 1.4k indexed citations. Recurring topics across this work include Neuroscience and Neuropharmacology Research (9 papers), Tryptophan and brain disorders (8 papers), Treatment of Major Depression (8 papers), Stress Responses and Cortisol (8 papers), Neuroendocrine regulation and behavior (6 papers), Memory and Neural Mechanisms (3 papers), Receptor Mechanisms and Signaling (2 papers) and Neurotransmitter Receptor Influence on Behavior (2 papers). The work is most often cited by research in Biological Psychiatry (549 citations), Behavioral Neuroscience (258 citations), Cellular and Molecular Neuroscience (593 citations), Pharmacology (506 citations) and Developmental Neuroscience (68 citations). Danielle M. Gerhard has collaborated with scholars based in United States, South Korea and Japan. Frequent co-authors include Ronald S. Duman, Eric S. Wohleb, Santosh Pothula, Marina R. Picciotto, Seth R. Taylor, Min Wu, Xiaoyuan Li, Rong-Jian Liu, Farhan Ali and Christopher Pittenger. Their work appears in journals such as Nature Communications, Neuropsychopharmacology, Behavioural Brain Research, Journal of Clinical Investigation and Biological Psychiatry.

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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