Mark Kon
Impact in
- Applied Mathematics top 2%
- Mathematical Analysis and Transform Methods
- Advanced Harmonic Analysis Research
- Biophysics top 2%
- Spectroscopy Techniques in Biomedical and Chemical Research
Papers in ⓘ
-
- Gene expression and cancer classification 11
- Bioinformatics and Genomic Networks 10
- Genomics and Chromatin Dynamics 6
- Machine Learning in Bioinformatics 5
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- Neural Networks and Applications 5
- Co-authors
- M. Holschneider (1 shared paper)Charles DeLisi (12 shared papers)Benjamin Allen (2 shared papers)Yaneer Bar‐Yam (1 shared paper)Shinuk Kim (6 shared papers)Archil Gulisashvili (1 shared paper)Dustin Holloway (6 shared papers)I. E. Segal (2 shared papers)
- Journals
- Journal of Complexity (6 papers)Bulletin of the American Mathematical Society (4 papers)Biology Direct (3 papers)Proceedings of the American Mathematical Society (3 papers)Physics Today (2 papers)
- Partner nations
- United StatesPolandSouth Korea
In The Last Decade
Mark Kon
65 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 152
- Applied Mathematics 305
- Biophysics 168
- Mathematical Physics 177
- Numerical Analysis 76
- Computer Vision and Pattern Recognition 268
Countries citing papers authored by Mark Kon
This map shows the geographic impact of Mark Kon'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 Mark Kon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark Kon more than expected).
Fields of papers citing papers by Mark Kon
This network shows the impact of papers produced by Mark Kon. 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 Mark Kon. The network helps show where Mark Kon may publish in the future.
Co-authors
The 25 scholars most cited alongside Mark Kon, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 70 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1996 | 349 | |
| 2 | 2009 | 126 | |
| 3 | 1993 | 105 | |
| 4 | 2012 | 100 | |
| 5 | 2012 | 85 | |
| 6 | 1996 | 60 | |
| 7 | 1994 | 54 | |
| 8 | 1994 | 50 | |
| 9 | 2011 | 50 | |
| 10 | 2000 | 50 | |
| 11 | 2018 | 46 | |
| 12 | 2015 | 44 | |
| 13 | Integrating genomic data to predict transcription factor binding. | 2005 | 41 |
| 14 | 2013 | 38 | |
| 15 | 2015 | 27 | |
| 16 | 2000 | 25 | |
| 17 | 2014 | 21 | |
| 18 | 2011 | 17 | |
| 19 | 2006 | 17 | |
| 20 | 2017 | 12 |
About Mark Kon
Mark Kon is a scholar working on Molecular Biology, Artificial Intelligence, Computational Theory and Mathematics, Computer Vision and Pattern Recognition and Mathematical Physics, having authored 70 papers that have together received 1.5k indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (12 papers), Gene expression and cancer classification (11 papers), Bioinformatics and Genomic Networks (10 papers), Advanced Mathematical Modeling in Engineering (6 papers), Genomics and Chromatin Dynamics (6 papers), Machine Learning in Bioinformatics (5 papers), Spectral Theory in Mathematical Physics (5 papers) and Neural Networks and Applications (5 papers). The work is most often cited by research in Applied Mathematics (305 citations), Biophysics (168 citations), Mathematical Physics (177 citations), Numerical Analysis (76 citations) and Computer Vision and Pattern Recognition (268 citations). Mark Kon has collaborated with scholars based in United States, Poland and South Korea. Frequent co-authors include M. Holschneider, Charles DeLisi, Benjamin Allen, Yaneer Bar‐Yam, Shinuk Kim, Archil Gulisashvili, Dustin Holloway, I. E. Segal, Max Diem and John C. Baez. Their work appears in journals such as Journal of Complexity, Bulletin of the American Mathematical Society, Biology Direct, Proceedings of the American Mathematical Society and Physics Today.
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.