Daniel Hähnke

618 citations
3 papers · 515 · 1 hit paper · h-index 3

Impact in

  • Genetics top 5%
    • Neurogenetic and Muscular Disorders Research
    • RNA Research and Splicing
    • Pluripotent Stem Cells Research
    • RNA and protein synthesis mechanisms

Papers in

Daniel Hähnke

3 papers receiving 494 citations

Daniel Hähnke's Hit Papers

SMN2 splicing modifiers improve motor function and longevity in mice with spinal muscular atrophy 2014 · 435 citations
4350+4+8Years since publication100200300400

Peers

Daniel Hähnke
Comparison fields: 5 of 30
  • Genetics 197
  • Molecular Biology 128
  • Computational Theory and Mathematics 24
  • Cognitive Neuroscience 30
  • Neurology 9
Replace Irene Hana Flønes with:
Irene Hana Flønes Norway
Carla Angelozzi Italy
Ianthe L. Pitout Australia
Spencer M. Goodman United States
Catherine Antar France
Jason Ruggiero United States
Heather L. Plasterer United States
Emilie Lauressergues France
Eric Villalón United States
Sarah D. Luppino United States
Daniel Hähnke relative to Irene Hana Flønes Norway Irene Hana Flønes's profile →
Citations per field
00.5×2×4×6×8.5×
Irene Hana Flønes · 1×
Citations per year

Countries citing papers authored by Daniel Hähnke

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Hähnke

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 9 scholars most cited alongside Daniel Hähnke, 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 Daniel Hähnke Line = papers co-authored together Daniel Hähnke links everyone, so they are left out of the graph.

All Works

3 of 3 papers shown
#Work
1
SMN2 splicing modifiers improve motor function and longevity in mice with spinal muscular atrophy
Hit paper breakdown →
2014435
2 201860
3 201820

About Daniel Hähnke

Daniel Hähnke is a scholar working on Genetics, Cognitive Neuroscience, Nuclear Energy and Engineering, Waste Management and Disposal and Infectious Diseases, having authored 3 papers that have together received 515 indexed citations. Recurring topics across this work include Neurogenetic and Muscular Disorders Research (2 papers) and Neural dynamics and brain function (1 paper). The work is most often cited by research in Genetics (197 citations), Molecular Biology (128 citations), Computational Theory and Mathematics (24 citations), Cognitive Neuroscience (30 citations) and Neurology (9 citations). Daniel Hähnke has collaborated with scholars based in Switzerland, United States and Germany. Frequent co-authors include Andreas Nieder, Simon N. Jacob, Friedrich Metzger, Martin Ebeling, Nicole Hellbach, Kathleen D. McCarthy, Uli Schmidt, Carolin Thomas and Samuel A. LaBarge. Their work appears in journals such as PLoS ONE, Science and Neuron.

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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