Danielle Feng

1.2k citations
13 papers · 847 · h-index 11

Impact in

  • Biophysics top 1%
    • Advanced Fluorescence Microscopy Techniques
    • Neuroscience and Neuropharmacology Research
    • Photoreceptor and optogenetics research
    • Neuroscience and Neural Engineering

Papers in

Danielle Feng

12 papers receiving 838 citations

Peers

Danielle Feng
Comparison fields: 5 of 91
  • Biophysics 205
  • Cellular and Molecular Neuroscience 290
  • Acoustics and Ultrasonics 13
  • Endocrine and Autonomic Systems 65
  • Cognitive Neuroscience 185
Replace Jennifer B. Treweek with:
Jennifer B. Treweek United States
Hansjörg Kasper Switzerland
Sandhiya Kalyanasundaram Italy
Jia‐Jia Liu China
Kiwamu Takemoto Japan
Christopher D. Deppmann United States
Rabih Moshourab Germany
Jan Tønnesen Spain
Katharine R. Smith United States
Markus Wölfel United States
Danielle Feng relative to Jennifer B. Treweek United States Jennifer B. Treweek's profile →
Citations per field
00.5×6.5×
Jennifer B. Treweek · 1×
Citations per year

Countries citing papers authored by Danielle Feng

Since Specialization
Citations

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

Fields of papers citing papers by Danielle Feng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

13 of 13 papers shown
#Work
1 2017341
2 2016103
3 201789
4 201680
5 201577
6 201446
7 201934
8 201722
9 201820
10 202214
11 201412
12 20189
13 20230

About Danielle Feng

Danielle Feng is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology, Neurology, Endocrine and Autonomic Systems and Cognitive Neuroscience, having authored 13 papers that have together received 847 indexed citations. Recurring topics across this work include Neuroscience and Neuropharmacology Research (3 papers), Circadian rhythm and melatonin (2 papers), Photoreceptor and optogenetics research (2 papers), Advanced Fluorescence Microscopy Techniques (2 papers), Parkinson's Disease Mechanisms and Treatments (2 papers), Autism Spectrum Disorder Research (1 paper), Alzheimer's disease research and treatments (1 paper) and Immunotherapy and Immune Responses (1 paper). The work is most often cited by research in Biophysics (205 citations), Cellular and Molecular Neuroscience (290 citations), Acoustics and Ultrasonics (13 citations), Endocrine and Autonomic Systems (65 citations) and Cognitive Neuroscience (185 citations). Danielle Feng has collaborated with scholars based in United States and China. Frequent co-authors include Xiqun Chen, Nozomi Nishimura, Dimitre G. Ouzounov, Tianyu Wang, Nicholas G. Horton, Chris Xu, Jacob Reimer, Andreas S. Tolias, Mengran Wang and Yu‐Ting Cheng. Their work appears in journals such as EBioMedicine, PLoS ONE, Nature Methods, Molecular Neurodegeneration and Annals of Clinical and Translational Neurology.

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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