Dan Ehninger

7.1k citations
87 papers · 4.7k indexed · 1 hit paper · h-index 34

Dan Ehninger

85 papers receiving 4.6k citations

Hit Papers

Reversal of learning deficits in a Tsc2+/− mouse model of...6512008202620142020200400600

Peers

Dan Ehninger
Comparison fields: 5 of 136
  • Developmental Neuroscience 1.1k
  • Aging 206
  • Neurology 595
  • Cellular and Molecular Neuroscience 1.2k
  • Behavioral Neuroscience 235
Replace Farahnaz Sananbenesi with:
Farahnaz Sananbenesi Germany
Jinsoo Seo South Korea
Ji‐Song Guan China
Gregor Bieri United States
Ivana Delalle United States
Alexander A. Sosunov United States
Diane C. Lagace Canada
Victoria M. Perreau Australia
Dan Ehninger relative to Farahnaz Sananbenesi Germany Farahnaz Sananbenesi's profile →
Citations per field
00.5×
Farahnaz Sananbenesi · 1×
Citations per year

Countries citing papers authored by Dan Ehninger

Since Specialization
Citations

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

Fields of papers citing papers by Dan Ehninger

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20252
2 20244
3 20241
4 20236
5 202320
6 20227
7 202215
8 20217
9 202088
10 202047
11 20206
12 201717
13 20179
14 201558
15 201385
16 201189
17 2010241
18 200917
19
Reversal of learning deficits in a Tsc2+/− mouse model of tuberous sclerosisbreakdown →
2008651
20 2007144

About Dan Ehninger

Dan Ehninger is a scholar working on Aging, Developmental Neuroscience, Cellular and Molecular Neuroscience, Physiology and Cognitive Neuroscience, having authored 87 papers that have together received 4.7k indexed citations. Recurring topics across this work include Neuroscience and Neuropharmacology Research (23 papers), Alzheimer's disease research and treatments (12 papers), Genetics, Aging, and Longevity in Model Organisms (10 papers), Memory and Neural Mechanisms (9 papers), Neurogenesis and neuroplasticity mechanisms (9 papers), Mitochondrial Function and Pathology (8 papers), Genetics and Neurodevelopmental Disorders (8 papers) and Neural dynamics and brain function (7 papers). The work is most often cited by research in Developmental Neuroscience (1.1k citations), Aging (206 citations), Neurology (595 citations), Cellular and Molecular Neuroscience (1.2k citations) and Behavioral Neuroscience (235 citations). Dan Ehninger has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include Alcino J. Silva, Gerd Kempermann, Weidong Li, Yu Zhou, Carrie Shilyansky, Golo Kronenberg, David J. Kwiatkowski, Vijaya Ramesh, Sangyeul Han and Kan Xie. Their work appears in journals such as Scientific Reports, Neural Plasticity, Mechanisms of Ageing and Development, Journal of Visualized Experiments and Cell Death Discovery.

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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