David Dao

42 papers receiving 2.5k citations

Peers

David Dao
Comparison fields: 5 of 149
  • Biological Psychiatry 296
  • Behavioral Neuroscience 303
  • Cellular and Molecular Neuroscience 446
  • Developmental Neuroscience 93
  • Neurology 154
Replace Xiaoli Qi with:
Xiaoli Qi China
Ping Liu New Zealand
Wenhua Zhang China
Simon T. Bate United Kingdom
Konrad Rejdak Poland
Steven F. Grieco United States
Bing Li China
Jesús A. Angulo United States
Takeshi Hashimoto Japan
Tao Lu China
David Dao relative to Xiaoli Qi China Xiaoli Qi's profile →
Citations per field
00.5×1.6×
Xiaoli Qi · 1×
Citations per year

Countries citing papers authored by David Dao

Since Specialization
Citations

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

Fields of papers citing papers by David Dao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011417
2 2011415
3 2009385
4 2012216
5 2010137
6 2019117
7 2019102
8 2012101
9 201695
10 201675
11 201268
12 201864
13 201158
14 201948
15 201930
16 202227
17 201725
18 202219
19 201519
20 202115

About David Dao

David Dao is a scholar working on Molecular Biology, Ophthalmology, Radiology, Nuclear Medicine and Imaging, Cellular and Molecular Neuroscience and Artificial Intelligence, having authored 44 papers that have together received 2.5k indexed citations. Recurring topics across this work include Retinal Diseases and Treatments (8 papers), Neurotransmitter Receptor Influence on Behavior (4 papers), Retinal and Macular Surgery (4 papers), Gut microbiota and health (3 papers), Receptor Mechanisms and Signaling (3 papers), Scientific Computing and Data Management (3 papers), Glaucoma and retinal disorders (3 papers) and Computational Drug Discovery Methods (3 papers). The work is most often cited by research in Biological Psychiatry (296 citations), Behavioral Neuroscience (303 citations), Cellular and Molecular Neuroscience (446 citations), Developmental Neuroscience (93 citations) and Neurology (154 citations). David Dao has collaborated with scholars based in United States, Switzerland and Germany. Frequent co-authors include Todd D. Gould, Chantelle E. Terrillion, Sean C. Piantadosi, Adem Can, Colleen E. Kovacsics, Michal Arad, Dawn Song, Nikolai M. Soldatov, Robert J. Smith and Jane Hung. Their work appears in journals such as Journal of Visualized Experiments, Investigative Ophthalmology & Visual Science, Proceedings of the VLDB Endowment, Cells and Translational Vision Science & Technology.

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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