Eric R. Greene
Impact in
- Health Informatics top 5%
- Molecular Biology top 10%
- Ubiquitin and proteasome pathways
- RNA and protein synthesis mechanisms
- Machine Learning in Bioinformatics
- Protein Structure and Dynamics
- Glycosylation and Glycoproteins Research
Papers in
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- Ubiquitin and proteasome pathways 4
- RNA and protein synthesis mechanisms 2
- Glycosylation and Glycoproteins Research 2
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- Autophagy in Disease and Therapy 3
- Co-authors
- Andreas Martin (4 shared papers)Ken C. Dong (2 shared papers)Ellen A. Goodall (2 shared papers)Erik Jönsson (1 shared paper)Jared A.M. Bard (1 shared paper)Nikhil Naik (1 shared paper)Caiming Xiong (1 shared paper)James M. Holton (1 shared paper)
- Journals
- Nature Chemical Biology (1 paper)Nature Biotechnology (1 paper)Annual Review of Biochemistry (1 paper)Proceedings of the National Academy of Sciences (1 paper)Biochemistry (1 paper)
- Partner nations
- United StatesJordan
In The Last Decade
Eric R. Greene
9 papers receiving 1.4k citations
Eric R. Greene's Hit Papers
Peers
Comparison fields: 5 of 113
- Health Informatics 22
- Molecular Biology 1.1k
- Cell Biology 175
- Biotechnology 81
- Oncology 168
Countries citing papers authored by Eric R. Greene
This map shows the geographic impact of Eric R. Greene'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 Eric R. Greene with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric R. Greene more than expected).
Fields of papers citing papers by Eric R. Greene
This network shows the impact of papers produced by Eric R. Greene. 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 Eric R. Greene. The network helps show where Eric R. Greene may publish in the future.
Co-authors
The 25 scholars most cited alongside Eric R. Greene, 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 | Structure and Function of the 26S Proteasome Hit paper breakdown → | 2018 | 587 |
| 2 | Large language models generate functional protein sequences across diverse families Hit paper breakdown → | 2023 | 566 |
| 3 | 2014 | 78 | |
| 4 | 2015 | 39 | |
| 5 | 2020 | 39 | |
| 6 | 2019 | 38 | |
| 7 | 2015 | 29 | |
| 8 | 2019 | 20 | |
| 9 | 2025 | 8 |
About Eric R. Greene
Eric R. Greene is a scholar working on Molecular Biology, Epidemiology, Organic Chemistry, Cell Biology and Biotechnology, having authored 9 papers that have together received 1.4k indexed citations. Recurring topics across this work include Ubiquitin and proteasome pathways (4 papers), Autophagy in Disease and Therapy (3 papers), RNA and protein synthesis mechanisms (2 papers), Glycosylation and Glycoproteins Research (2 papers), Endoplasmic Reticulum Stress and Disease (2 papers), Enzyme Production and Characterization (2 papers), Carbohydrate Chemistry and Synthesis (2 papers) and Biofuel production and bioconversion (2 papers). The work is most often cited by research in Health Informatics (22 citations), Molecular Biology (1.1k citations), Cell Biology (175 citations), Biotechnology (81 citations) and Oncology (168 citations). Eric R. Greene has collaborated with scholars based in United States and Jordan. Frequent co-authors include Andreas Martin, Ken C. Dong, Ellen A. Goodall, Erik Jönsson, Jared A.M. Bard, Nikhil Naik, Caiming Xiong, James M. Holton, James S. Fraser and Ali Madani. Their work appears in journals such as Nature Chemical Biology, Nature Biotechnology, Annual Review of Biochemistry, Proceedings of the National Academy of Sciences and Biochemistry.
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.