Konstantinos Kelaidonis
- Molecular Biology
- Infectious Diseases
- Computational Theory and Mathematics top 10%
- Cardiology and Cardiovascular Medicine
- Organic Chemistry
- Co-authors
- John MatsoukasGraham J. MooreVasso ApostolopoulosThomas MavromoustakosAnthony ZulliChristos T. ChasapisHarry RidgwayLaura Kate Gadanec
- Topics
- Receptor Mechanisms and Signaling (8 papers)SARS-CoV-2 and COVID-19 Research (7 papers)Computational Drug Discovery Methods (7 papers)
In The Last Decade
Konstantinos Kelaidonis
19 papers receiving 214 citations
Peers
Comparison fields: 5 of 65
- Molecular Biology 96
- Infectious Diseases 79
- Computational Theory and Mathematics 62
- Cardiology and Cardiovascular Medicine 43
- Organic Chemistry 33
Countries citing papers authored by Konstantinos Kelaidonis
This map shows the geographic impact of Konstantinos Kelaidonis'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 Konstantinos Kelaidonis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Konstantinos Kelaidonis more than expected).
Fields of papers citing papers by Konstantinos Kelaidonis
This network shows the impact of papers produced by Konstantinos Kelaidonis. 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 Konstantinos Kelaidonis. The network helps show where Konstantinos Kelaidonis may publish in the future.
Co-authorship network of co-authors of Konstantinos Kelaidonis
This figure shows the co-authorship network connecting the top 25 collaborators of Konstantinos Kelaidonis. A scholar is included among the top collaborators of Konstantinos Kelaidonis based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Konstantinos Kelaidonis. Konstantinos Kelaidonis is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 3 | |
| 3 | 1 | |
| 4 | 19 | |
| 5 | 9 | |
| 6 | 9 | |
| 7 | 16 | |
| 8 | 8 | |
| 9 | 10 | |
| 10 | 26 | |
| 11 | 31 | |
| 12 | 2 | |
| 13 | 7 | |
| 14 | 12 | |
| 15 | 20 | |
| 16 | 7 | |
| 17 | 10 | |
| 18 | 20 | |
| 19 | 1 |
About Konstantinos Kelaidonis
Konstantinos Kelaidonis is a scholar working on Infectious Diseases, Computational Theory and Mathematics and Physiology, having authored 19 papers that have together received 215 indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (8 papers), SARS-CoV-2 and COVID-19 Research (7 papers) and Computational Drug Discovery Methods (7 papers). The work is most often cited by research in Infectious Diseases (79 citations), Computational Theory and Mathematics (62 citations) and Pharmacology (18 citations). Konstantinos Kelaidonis has collaborated with scholars based in Greece, Canada and Australia. Frequent co-authors include John Matsoukas, Graham J. Moore, Vasso Apostolopoulos, Thomas Mavromoustakos, Anthony Zulli, Christos T. Chasapis, Harry Ridgway, Laura Kate Gadanec, Sotirios Tsiodras and Minos–Timotheos Matsoukas. Their work appears in journals such as International Journal of Molecular Sciences, Molecules and Amino Acids.
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.