Daniel J. Hoeppner
- Developmental Neuroscience top 1%
- Neurogenesis and neuroplasticity mechanisms 4
- Aging top 2%
- Genetics, Aging, and Longevity in Model Organisms 3
- Molecular Biology top 5%
- Pluripotent Stem Cells Research 7
- Epigenetics and DNA Methylation 3
- CRISPR and Genetic Engineering 3
- Cancer Research top 10%
- Neurology top 5%
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- Cell Image Analysis Techniques 6
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- Image Processing Techniques and Applications 4
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- Medical Image Segmentation Techniques 3
- Co-authors
- Ronald D.G. McKayRea RavinMichael O. HengartnerAndreas Androutsellis‐TheotokisFrank SoldnerRalf SchnabelSoo-Kyung BaeRaja Kittappa
- Partner nations
- United StatesUnited KingdomSwitzerland
In The Last Decade
Daniel J. Hoeppner
25 papers receiving 2.6k citations
Hit Papers
Peers
Comparison fields: 5 of 129
- Developmental Neuroscience 391
- Aging 151
- Molecular Biology 1.8k
- Cancer Research 292
- Neurology 139
Countries citing papers authored by Daniel J. Hoeppner
This map shows the geographic impact of Daniel J. Hoeppner'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 J. Hoeppner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel J. Hoeppner more than expected).
Fields of papers citing papers by Daniel J. Hoeppner
This network shows the impact of papers produced by Daniel J. Hoeppner. 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 J. Hoeppner. The network helps show where Daniel J. Hoeppner may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Daniel J. Hoeppner, 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 | 2020 | 61 | |
| 2 | 2020 | 6 | |
| 3 | 2020 | 10 | |
| 4 | 2019 | 2 | |
| 5 | 2019 | 66 | |
| 6 | 2018 | 18 | |
| 7 | 2016 | 14 | |
| 8 | 2016 | 108 | |
| 9 | 2012 | 34 | |
| 10 | 2011 | 22 | |
| 11 | 2011 | 110 | |
| 12 | 2008 | 16 | |
| 13 | Global Transcription in Pluripotent Embryonic Stem Cellsbreakdown → | 2008 | 512 |
| 14 | 2008 | 82 | |
| 15 | 2007 | 107 | |
| 16 | Notch signalling regulates stem cell numbers in vitro and in vivobreakdown → | 2006 | 794 |
| 17 | 2004 | 25 | |
| 18 | 2001 | 238 | |
| 19 | 1997 | 258 | |
| 20 | 1996 | 7 |
About Daniel J. Hoeppner
Daniel J. Hoeppner is a scholar working on Aging, Biophysics, Developmental Neuroscience, Media Technology and Computer Vision and Pattern Recognition, having authored 25 papers that have together received 2.6k indexed citations. Recurring topics across this work include Pluripotent Stem Cells Research (7 papers), Cell Image Analysis Techniques (6 papers), Image Processing Techniques and Applications (4 papers), Neurogenesis and neuroplasticity mechanisms (4 papers), Epigenetics and DNA Methylation (3 papers), Genetics, Aging, and Longevity in Model Organisms (3 papers), Medical Image Segmentation Techniques (3 papers) and CRISPR and Genetic Engineering (3 papers). The work is most often cited by research in Developmental Neuroscience (391 citations), Aging (151 citations), Molecular Biology (1.8k citations), Cancer Research (292 citations) and Neurology (139 citations). Daniel J. Hoeppner has collaborated with scholars based in United States, United Kingdom and Switzerland. Frequent co-authors include Ronald D.G. McKay, Rea Ravin, Michael O. Hengartner, Andreas Androutsellis‐Theotokis, Frank Soldner, Ralf Schnabel, Soo-Kyung Bae, Raja Kittappa, Ronen R. Leker and Steven Poser. Their work appears in journals such as Nature, Stem Cells, Cell stem cell, Scientific Reports and Frontiers in Psychiatry.
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.