Daniel C. Factor
Impact in
- Developmental Neuroscience top 2%
- Neurogenesis and neuroplasticity mechanisms
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- Pluripotent Stem Cells Research
- CRISPR and Genetic Engineering
- Epigenetics and DNA Methylation
- RNA Research and Splicing
Papers in
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- Pluripotent Stem Cells Research 4
- CRISPR and Genetic Engineering 4
- Protein Degradation and Inhibitors 2
- Genomics and Chromatin Dynamics 2
- RNA Research and Splicing 2
- Ubiquitin and proteasome pathways 2
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- Neurogenesis and neuroplasticity mechanisms 5
- Co-authors
- Paul J. Tesar (9 shared papers)Robert H. Miller (2 shared papers)Zachary S. Nevin (3 shared papers)Angela M. Lager (2 shared papers)Valentina Fossati (2 shared papers)Panagiotis Douvaras (2 shared papers)Fadi J. Najm (2 shared papers)Anita Zaremba (1 shared paper)
- Journals
- Nature Methods (1 paper)The American Journal of Human Genetics (1 paper)Glia (1 paper)Frontiers in Neuroscience (1 paper)Cell stem cell (1 paper)
- Partner nations
- United StatesJapanDenmark
In The Last Decade
Daniel C. Factor
11 papers receiving 768 citations
Peers
Comparison fields: 5 of 64
- Developmental Neuroscience 274
- Molecular Biology 634
- Neurology 58
- Cellular and Molecular Neuroscience 121
- Cancer Research 97
Countries citing papers authored by Daniel C. Factor
This map shows the geographic impact of Daniel C. Factor'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 C. Factor with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel C. Factor more than expected).
Fields of papers citing papers by Daniel C. Factor
This network shows the impact of papers produced by Daniel C. Factor. 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 C. Factor. The network helps show where Daniel C. Factor may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel C. Factor, 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 | 2018 | 240 | |
| 2 | 2013 | 204 | |
| 3 | 2014 | 113 | |
| 4 | 2012 | 60 | |
| 5 | 2017 | 49 | |
| 6 | 2016 | 49 | |
| 7 | 2018 | 27 | |
| 8 | 2018 | 18 | |
| 9 | 2019 | 12 | |
| 10 | 2013 | 3 | |
| 11 | 2017 | 1 |
About Daniel C. Factor
Daniel C. Factor is a scholar working on Molecular Biology, Developmental Neuroscience, Cancer Research, Oncology and Hematology, having authored 11 papers that have together received 776 indexed citations. Recurring topics across this work include MicroRNA in disease regulation (5 papers), Neurogenesis and neuroplasticity mechanisms (5 papers), Pluripotent Stem Cells Research (4 papers), CRISPR and Genetic Engineering (4 papers), Protein Degradation and Inhibitors (2 papers), Genomics and Chromatin Dynamics (2 papers), RNA Research and Splicing (2 papers) and Ubiquitin and proteasome pathways (2 papers). The work is most often cited by research in Developmental Neuroscience (274 citations), Molecular Biology (634 citations), Neurology (58 citations), Cellular and Molecular Neuroscience (121 citations) and Cancer Research (97 citations). Daniel C. Factor has collaborated with scholars based in United States, Japan and Denmark. Frequent co-authors include Paul J. Tesar, Robert H. Miller, Zachary S. Nevin, Angela M. Lager, Valentina Fossati, Panagiotis Douvaras, Fadi J. Najm, Anita Zaremba, Andrew V. Caprariello and Tadao Maeda. Their work appears in journals such as Nature Methods, The American Journal of Human Genetics, Glia, Frontiers in Neuroscience and Cell stem cell.
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.