Daniel W. Allison
Impact in
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- Neuroscience and Neuropharmacology Research
- Photoreceptor and optogenetics research
- Developmental Neuroscience top 5%
- Neurogenesis and neuroplasticity mechanisms
Papers in
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- RNA Interference and Gene Delivery 2
- Pluripotent Stem Cells Research 2
- CRISPR and Genetic Engineering 2
- Viral Infectious Diseases and Gene Expression in Insects 1
- Mitochondrial Function and Pathology 1
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- Neuroscience and Neuropharmacology Research 3
- Co-authors
- Ann Marie Craig (4 shared papers)Vladimir I. Gelfand (2 shared papers)Ilan Spector (1 shared paper)Morgan Sheng (2 shared papers)Juli G. Valtschanoff (2 shared papers)Richard J. Weinberg (2 shared papers)Adam S. Chervin (1 shared paper)Tarun M. Kapoor (1 shared paper)
- Journals
- Journal of Neuroscience (3 papers)Neuron (1 paper)Methods in molecular biology (1 paper)BioProcessing Journal (1 paper)PubMed (1 paper)
- Partner nations
- United StatesSouth Korea
In The Last Decade
Daniel W. Allison
7 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 74
- Cellular and Molecular Neuroscience 799
- Developmental Neuroscience 116
- Cell Biology 358
- Molecular Biology 714
- Neurology 74
Countries citing papers authored by Daniel W. Allison
This map shows the geographic impact of Daniel W. Allison'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 W. Allison with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel W. Allison more than expected).
Fields of papers citing papers by Daniel W. Allison
This network shows the impact of papers produced by Daniel W. Allison. 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 W. Allison. The network helps show where Daniel W. Allison may publish in the future.
Co-authors
The 15 scholars most cited alongside Daniel W. Allison, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 1998 | 476 | |
| 2 | 1998 | 258 | |
| 3 | 2000 | 203 | |
| 4 | 2000 | 193 | |
| 5 | Gene Editing in Human Pluripotent Stem Cells: Choosing the Correct Path. | 2015 | 10 |
| 6 | 2003 | 2 | |
| 7 | 2016 | 1 |
About Daniel W. Allison
Daniel W. Allison is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Cell Biology, Developmental Neuroscience and Cognitive Neuroscience, having authored 7 papers that have together received 1.1k indexed citations. Recurring topics across this work include Neuroscience and Neuropharmacology Research (3 papers), RNA Interference and Gene Delivery (2 papers), Neurogenesis and neuroplasticity mechanisms (2 papers), Pluripotent Stem Cells Research (2 papers), CRISPR and Genetic Engineering (2 papers), Viral Infectious Diseases and Gene Expression in Insects (1 paper), Monoclonal and Polyclonal Antibodies Research (1 paper) and Mitochondrial Function and Pathology (1 paper). The work is most often cited by research in Cellular and Molecular Neuroscience (799 citations), Developmental Neuroscience (116 citations), Cell Biology (358 citations), Molecular Biology (714 citations) and Neurology (74 citations). Daniel W. Allison has collaborated with scholars based in United States and South Korea. Frequent co-authors include Ann Marie Craig, Vladimir I. Gelfand, Ilan Spector, Morgan Sheng, Juli G. Valtschanoff, Richard J. Weinberg, Adam S. Chervin, Tarun M. Kapoor, Martin Niethammer and Scott Naisbitt. Their work appears in journals such as Journal of Neuroscience, Neuron, Methods in molecular biology, BioProcessing Journal and PubMed.
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.