Glen E. Kellogg
Impact in
- Computational Theory and Mathematics top 0.2%
- Computational Drug Discovery Methods
- Molecular Biology top 2%
- Protein Structure and Dynamics
- Receptor Mechanisms and Signaling
- DNA and Nucleic Acid Chemistry
Papers in
-
- Computational Drug Discovery Methods 35
-
- Protein Structure and Dynamics 47
- DNA and Nucleic Acid Chemistry 8
- Receptor Mechanisms and Signaling 8
- Co-authors
- Donald J. AbrahamPietro CozziniAndrea MozzarelliMicaela FornabaioFrancesca SpyrakisSimon F. SemusAurijit SarkarDennis L. Lichtenberger
- Journals
- Journal of Medicinal Chemistry (14 papers)Bioorganic & Medicinal Chemistry (8 papers)Journal of Computer-Aided Molecular Design (8 papers)Bioorganic & Medicinal Chemistry Letters (6 papers)PLoS ONE (6 papers)
- Partner nations
- United StatesItalyAustralia
In The Last Decade
Glen E. Kellogg
138 papers receiving 4.8k citations
Peers
Comparison fields: 5 of 141
- Computational Theory and Mathematics 1.2k
- Molecular Biology 2.9k
- Organic Chemistry 918
- Spectroscopy 381
- Virology 104
Countries citing papers authored by Glen E. Kellogg
This map shows the geographic impact of Glen E. Kellogg'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 Glen E. Kellogg with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Glen E. Kellogg more than expected).
Fields of papers citing papers by Glen E. Kellogg
This network shows the impact of papers produced by Glen E. Kellogg. 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 Glen E. Kellogg. The network helps show where Glen E. Kellogg may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Glen E. Kellogg, 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 | 2 | |
| 2 | 2023 | 4 | |
| 3 | 2023 | 0 | |
| 4 | 2023 | 26 | |
| 5 | 2019 | 15 | |
| 6 | 2014 | 12 | |
| 7 | 2014 | 19 | |
| 8 | 2013 | 21 | |
| 9 | 2013 | 14 | |
| 10 | 2011 | 51 | |
| 11 | 2009 | 18 | |
| 12 | 2007 | 53 | |
| 13 | 2007 | 9 | |
| 14 | 2007 | 48 | |
| 15 | 2006 | 55 | |
| 16 | 2005 | 35 | |
| 17 | 2004 | 77 | |
| 18 | 2004 | 56 | |
| 19 | 1998 | 13 | |
| 20 | 1996 | 80 |
About Glen E. Kellogg
Glen E. Kellogg is a scholar working on Computational Theory and Mathematics, Molecular Biology, Virology, Cell Biology and Spectroscopy, having authored 143 papers that have together received 4.9k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (47 papers), Computational Drug Discovery Methods (35 papers), Enzyme Structure and Function (19 papers), DNA and Nucleic Acid Chemistry (8 papers), Receptor Mechanisms and Signaling (8 papers), Spectroscopy and Quantum Chemical Studies (7 papers), Hemoglobin structure and function (7 papers) and Synthesis and biological activity (6 papers). The work is most often cited by research in Computational Theory and Mathematics (1.2k citations), Molecular Biology (2.9k citations), Organic Chemistry (918 citations), Spectroscopy (381 citations) and Virology (104 citations). Glen E. Kellogg has collaborated with scholars based in United States, Italy and Australia. Frequent co-authors include Donald J. Abraham, Pietro Cozzini, Andrea Mozzarelli, Micaela Fornabaio, Francesca Spyrakis, Simon F. Semus, Aurijit Sarkar, Dennis L. Lichtenberger, Matteo Porotto and Anne Moscona. Their work appears in journals such as Journal of Medicinal Chemistry, Bioorganic & Medicinal Chemistry, Journal of Computer-Aided Molecular Design, Bioorganic & Medicinal Chemistry Letters and PLoS ONE.
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.