Mark Kon

2.3k citations
70 papers · 1.5k · h-index 18

Impact in

    • 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 7
    • Machine Learning in Bioinformatics 5
    • Genomics and Chromatin Dynamics 5
    • Neural Networks and Applications 5

Mark Kon

65 papers receiving 1.4k citations

Peers

Mark Kon
Comparison fields: 5 of 149
  • Applied Mathematics 306
  • Biophysics 165
  • Mathematical Physics 180
  • Numerical Analysis 77
  • Computer Vision and Pattern Recognition 266
Replace Bradley J. Lucier with:
Bradley J. Lucier United States
Peter Maaß Germany
Douglas P. Hardin United States
Dejan Slepčev United States
Markus Hegland Australia
Vladimir Spokoiny Germany
Gérard Kerkyacharian France
Wilfrid S. Kendall United Kingdom
Selim Esedoḡlu United States
Ajay Jasra United Kingdom
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Citations per field
00.5×2.9×
Bradley J. Lucier · 1×
Citations per year

Countries citing papers authored by Mark Kon

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Mark Kon Line = papers co-authored together Mark Kon links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 70 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1996348
2 2009130
3 1993106
4 2012100
5 201287
6 199663
7 199454
8 200051
9 201150
10 199450
11 201847
12 201545
13
Integrating genomic data to predict transcription factor binding.
200541
14 201338
15 201527
16 200025
17 201421
18 201117
19 200617
20 201712

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 (7 papers), Advanced Mathematical Modeling in Engineering (6 papers), Neural Networks and Applications (5 papers), Machine Learning in Bioinformatics (5 papers), Spectral Theory in Mathematical Physics (5 papers) and Genomics and Chromatin Dynamics (5 papers). The work is most often cited by research in Applied Mathematics (306 citations), Biophysics (165 citations), Mathematical Physics (180 citations), Numerical Analysis (77 citations) and Computer Vision and Pattern Recognition (266 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, I. E. Segal, Dustin Holloway, John C. Baez and Max Diem. 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 The Analyst.

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.

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