Christopher Gregg
- Genetics top 2%
- Genetic Syndromes and Imprinting 11
- Bacterial Genetics and Biotechnology 5
- Molecular Biology top 5%
- Epigenetics and DNA Methylation 10
- Glycosylation and Glycoproteins Research 6
- CRISPR and Genetic Engineering 6
- RNA and protein synthesis mechanisms 6
- Genomics and Chromatin Dynamics 5
- Aging top 10%
- Biotechnology top 10%
- Immunology top 10%
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- Adipose Tissue and Metabolism 4
- Co-authors
- Jiangwen ZhangDavid HaigCatherine DulacGeorge M. ChurchAjit VarkiNissi VarkiGary P. SchrothShujun Luo
- Cited by
- GeneticsMolecular BiologyAging
- Journals
- Cell Reports (6 papers)Science (5 papers)Proceedings of the National Academy of Sciences (4 papers)
- Partner nations
- United StatesUnited KingdomJapan
In The Last Decade
Christopher Gregg
35 papers receiving 2.5k citations
Peers
Comparison fields: 5 of 126
- Genetics 1.0k
- Molecular Biology 1.9k
- Aging 24
- Biotechnology 93
- Immunology 224
Countries citing papers authored by Christopher Gregg
This map shows the geographic impact of Christopher Gregg'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 Christopher Gregg with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christopher Gregg more than expected).
Fields of papers citing papers by Christopher Gregg
This network shows the impact of papers produced by Christopher Gregg. 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 Christopher Gregg. The network helps show where Christopher Gregg may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Christopher Gregg, 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 | 2025 | 1 | |
| 2 | 2023 | 14 | |
| 3 | 2021 | 40 | |
| 4 | 2020 | 89 | |
| 5 | 2019 | 11 | |
| 6 | 2019 | 12 | |
| 7 | 2019 | 15 | |
| 8 | 2018 | 44 | |
| 9 | 2018 | 17 | |
| 10 | 2018 | 28 | |
| 11 | 2017 | 102 | |
| 12 | 2017 | 26 | |
| 13 | 2016 | 45 | |
| 14 | 2015 | 311 | |
| 15 | 2015 | 60 | |
| 16 | 2014 | 10 | |
| 17 | 2010 | 393 | |
| 18 | 2010 | 260 | |
| 19 | 2010 | 12 | |
| 20 | 2009 | 88 |
About Christopher Gregg
Christopher Gregg is a scholar working on Genetics, Molecular Biology, Immunology, Sensory Systems and Cancer Research, having authored 35 papers that have together received 2.6k indexed citations. Recurring topics across this work include Genetic Syndromes and Imprinting (11 papers), Epigenetics and DNA Methylation (10 papers), Glycosylation and Glycoproteins Research (6 papers), CRISPR and Genetic Engineering (6 papers), RNA and protein synthesis mechanisms (6 papers), Bacterial Genetics and Biotechnology (5 papers), Genomics and Chromatin Dynamics (5 papers) and Adipose Tissue and Metabolism (4 papers). The work is most often cited by research in Genetics (1.0k citations), Molecular Biology (1.9k citations), Aging (24 citations), Biotechnology (93 citations) and Immunology (224 citations). Christopher Gregg has collaborated with scholars based in United States, United Kingdom and Japan. Frequent co-authors include Jiangwen Zhang, David Haig, Catherine Dulac, George M. Church, Ajit Varki, Nissi Varki, Gary P. Schroth, Shujun Luo, Brandon Weissbourd and J. G. Lajoie. Their work appears in journals such as Cell Reports, Science, Proceedings of the National Academy of Sciences, Nucleic Acids Research and iScience.
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.