Daniel Zeve
Impact in
- Physiology top 2%
- Adipose Tissue and Metabolism
- Genetics top 5%
- Mesenchymal stem cell research
Papers in
- Physiology 10
- Adipose Tissue and Metabolism 8
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- Bone Metabolism and Diseases 3
- Metabolism, Diabetes, and Cancer 2
- Wnt/β-catenin signaling in development and cancer 2
- Co-authors
- Jonathan M. Graff (10 shared papers)Jae Myoung Suh (5 shared papers)Wei Tang (3 shared papers)Michael Kyba (1 shared paper)Darko Bosnakovski (1 shared paper)Robert E. Hammer (1 shared paper)Michelle D. Tallquist (1 shared paper)Drew Stenesen (2 shared papers)
- Journals
- Nature Communications (3 papers)Cell Metabolism (3 papers)Molecular and Cellular Biology (2 papers)Developmental Cell (1 paper)Alcohol (1 paper)
- Partner nations
- United StatesChinaTürkiye
In The Last Decade
Daniel Zeve
25 papers receiving 2.1k citations
Daniel Zeve's Hit Papers
Peers
Comparison fields: 5 of 108
- Physiology 846
- Genetics 290
- Epidemiology 651
- Aging 25
- Endocrine and Autonomic Systems 86
Countries citing papers authored by Daniel Zeve
This map shows the geographic impact of Daniel Zeve'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 Zeve with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Zeve more than expected).
Fields of papers citing papers by Daniel Zeve
This network shows the impact of papers produced by Daniel Zeve. 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 Zeve. The network helps show where Daniel Zeve may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Zeve, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | White Fat Progenitor Cells Reside in the Adipose Vasculature Hit paper breakdown → | 2008 | 872 |
| 2 | 2013 | 251 | |
| 3 | 2013 | 216 | |
| 4 | 2011 | 156 | |
| 5 | 2009 | 83 | |
| 6 | 2011 | 76 | |
| 7 | 2007 | 72 | |
| 8 | 2016 | 66 | |
| 9 | 2012 | 64 | |
| 10 | 2005 | 51 | |
| 11 | 2014 | 45 | |
| 12 | 2022 | 42 | |
| 13 | 2011 | 41 | |
| 14 | 2022 | 27 | |
| 15 | 2022 | 21 | |
| 16 | 2003 | 15 | |
| 17 | 2023 | 15 | |
| 18 | 2016 | 11 | |
| 19 | 2007 | 8 | |
| 20 | 2011 | 8 |
About Daniel Zeve
Daniel Zeve is a scholar working on Physiology, Molecular Biology, Epidemiology, Surgery and Cellular and Molecular Neuroscience, having authored 26 papers that have together received 2.2k indexed citations. Recurring topics across this work include Adipose Tissue and Metabolism (8 papers), Adipokines, Inflammation, and Metabolic Diseases (6 papers), Pancreatic function and diabetes (4 papers), Bone Metabolism and Diseases (3 papers), Prenatal Substance Exposure Effects (2 papers), Neuroscience and Neuropharmacology Research (2 papers), Metabolism, Diabetes, and Cancer (2 papers) and Wnt/β-catenin signaling in development and cancer (2 papers). The work is most often cited by research in Physiology (846 citations), Genetics (290 citations), Epidemiology (651 citations), Aging (25 citations) and Endocrine and Autonomic Systems (86 citations). Daniel Zeve has collaborated with scholars based in United States, China and Türkiye. Frequent co-authors include Jonathan M. Graff, Jae Myoung Suh, Wei Tang, Michael Kyba, Darko Bosnakovski, Robert E. Hammer, Michelle D. Tallquist, Drew Stenesen, Daniel C. Berry and Wei Tang. Their work appears in journals such as Nature Communications, Cell Metabolism, Molecular and Cellular Biology, Developmental Cell and Alcohol.
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.