Eric A. Sigel
Impact in
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- Chemical Synthesis and Analysis
- Advanced biosensing and bioanalysis techniques
- RNA and protein synthesis mechanisms
- Genomics and Chromatin Dynamics
- Protein Degradation and Inhibitors
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- Click Chemistry and Applications
Papers in
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- Chemical Synthesis and Analysis 3
- PI3K/AKT/mTOR signaling in cancer 2
- Machine Learning in Bioinformatics 1
- Sphingolipid Metabolism and Signaling 1
- Enzyme function and inhibition 1
- Cancer therapeutics and mechanisms 1
- Co-authors
- Matthew Clark (5 shared papers)Anthony D. Keefe (5 shared papers)John W. Cuozzo (5 shared papers)Diana Gikunju (3 shared papers)Sevan Habeshian (3 shared papers)Marie-Aude Guié (3 shared papers)Heather A. Thomson (2 shared papers)Christoph E. Dumelin (2 shared papers)
- Journals
- Journal of Medicinal Chemistry (2 papers)Scientific Reports (1 paper)Journal of Cell Science (1 paper)Proceedings of the National Academy of Sciences (1 paper)ChemBioChem (1 paper)
- Partner nations
- United StatesSwitzerlandIndia
In The Last Decade
Eric A. Sigel
7 papers receiving 374 citations
Peers
Comparison fields: 5 of 45
- Molecular Biology 353
- Organic Chemistry 139
- Radiology, Nuclear Medicine and Imaging 101
- Computational Theory and Mathematics 53
- Molecular Medicine 6
Countries citing papers authored by Eric A. Sigel
This map shows the geographic impact of Eric A. Sigel'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 A. Sigel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric A. Sigel more than expected).
Fields of papers citing papers by Eric A. Sigel
This network shows the impact of papers produced by Eric A. Sigel. 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 A. Sigel. The network helps show where Eric A. Sigel may publish in the future.
Co-authors
The 25 scholars most cited alongside Eric A. Sigel, 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 | 2015 | 87 | |
| 2 | 2020 | 85 | |
| 3 | 2020 | 79 | |
| 4 | 1997 | 52 | |
| 5 | 2017 | 51 | |
| 6 | 2016 | 46 | |
| 7 | 2025 | 2 |
About Eric A. Sigel
Eric A. Sigel is a scholar working on Molecular Biology, Infectious Diseases, Organic Chemistry, Genetics and Molecular Medicine, having authored 7 papers that have together received 402 indexed citations. Recurring topics across this work include Chemical Synthesis and Analysis (3 papers), PI3K/AKT/mTOR signaling in cancer (2 papers), Machine Learning in Bioinformatics (1 paper), Sphingolipid Metabolism and Signaling (1 paper), Enzyme function and inhibition (1 paper), Cancer therapeutics and mechanisms (1 paper), Click Chemistry and Applications (1 paper) and Chronic Lymphocytic Leukemia Research (1 paper). The work is most often cited by research in Molecular Biology (353 citations), Organic Chemistry (139 citations), Radiology, Nuclear Medicine and Imaging (101 citations), Computational Theory and Mathematics (53 citations) and Molecular Medicine (6 citations). Eric A. Sigel has collaborated with scholars based in United States, Switzerland and India. Frequent co-authors include Matthew Clark, Anthony D. Keefe, John W. Cuozzo, Diana Gikunju, Sevan Habeshian, Marie-Aude Guié, Heather A. Thomson, Christoph E. Dumelin, Christopher D. Hupp and Mark S. Mooseker. Their work appears in journals such as Journal of Medicinal Chemistry, Scientific Reports, Journal of Cell Science, Proceedings of the National Academy of Sciences and ChemBioChem.
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.