John T. Egan
Impact in
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- Cancer-related molecular mechanisms research
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- RNA and protein synthesis mechanisms
- RNA Research and Splicing
- RNA modifications and cancer
- CRISPR and Genetic Engineering
- Genomics and Chromatin Dynamics
Papers in
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- DNA and Nucleic Acid Chemistry 7
- RNA and protein synthesis mechanisms 5
- Protein Structure and Dynamics 3
- Genomics and Chromatin Dynamics 2
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- Scientific Computing and Data Management 3
- Co-authors
- Keith E. Shearwin (1 shared paper)Kenneth C. Scott-Brown (1 shared paper)P. George Lovell (1 shared paper)R. D. Macelroy (8 shared papers)Stanley K. Burt (2 shared papers)Robert Rein (8 shared papers)Shlomo Nir (2 shared papers)Silvano P. Colombano (1 shared paper)
- Journals
- International Journal of Quantum Chemistry (5 papers)Computers & Graphics (2 papers)Scientific Reports (1 paper)Biosystems (1 paper)Journal of Computational Chemistry (1 paper)
- Partner nations
- United StatesUnited KingdomAustralia
In The Last Decade
John T. Egan
11 papers receiving 484 citations
Peers
Comparison fields: 5 of 76
- Cancer Research 89
- Molecular Biology 392
- Genetics 135
- Virology 13
- Endocrinology 11
Countries citing papers authored by John T. Egan
This map shows the geographic impact of John T. Egan'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 John T. Egan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John T. Egan more than expected).
Fields of papers citing papers by John T. Egan
This network shows the impact of papers produced by John T. Egan. 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 John T. Egan. The network helps show where John T. Egan may publish in the future.
Co-authors
The 8 scholars most cited alongside John T. Egan, 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 | 2005 | 434 | |
| 2 | 2016 | 28 | |
| 3 | 1977 | 10 | |
| 4 | 1982 | 8 | |
| 5 | 1983 | 3 | |
| 6 | 1980 | 2 | |
| 7 | 1984 | 1 | |
| 8 | 2009 | 1 | |
| 9 | 1976 | 1 | |
| 10 | 2009 | 1 | |
| 11 | A model for stereospecific recognition of purines as an element of a DNA polypeptide recognition code | 1978 | 1 |
| 12 | 1984 | 1 | |
| 13 | 2009 | 0 | |
| 14 | 2009 | 0 | |
| 15 | 2009 | 0 |
About John T. Egan
John T. Egan is a scholar working on Molecular Biology, Information Systems and Management, Physical and Theoretical Chemistry, Genetics and Spectroscopy, having authored 15 papers that have together received 491 indexed citations. Recurring topics across this work include DNA and Nucleic Acid Chemistry (7 papers), RNA and protein synthesis mechanisms (5 papers), Various Chemistry Research Topics (3 papers), Scientific Computing and Data Management (3 papers), Protein Structure and Dynamics (3 papers), Bacterial Genetics and Biotechnology (2 papers), Genomics and Chromatin Dynamics (2 papers) and Chemical Thermodynamics and Molecular Structure (1 paper). The work is most often cited by research in Cancer Research (89 citations), Molecular Biology (392 citations), Genetics (135 citations), Virology (13 citations) and Endocrinology (11 citations). John T. Egan has collaborated with scholars based in United States, United Kingdom and Australia. Frequent co-authors include Keith E. Shearwin, Kenneth C. Scott-Brown, P. George Lovell, R. D. Macelroy, Stanley K. Burt, Robert Rein, Shlomo Nir and Silvano P. Colombano. Their work appears in journals such as International Journal of Quantum Chemistry, Computers & Graphics, Scientific Reports, Biosystems and Journal of Computational Chemistry.
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.