Mark Kon
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Explore the profile of Mark Kon including associated specialties, affiliations and a list of published articles.
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Articles
19
Citations
245
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Recent Articles
1.
Chen N, Yu D, Beglov D, Kon M, Castrillon-Candas J
ArXiv
. 2024 Feb;
PMID: 38344224
Recent advancements in protein docking site prediction have highlighted the limitations of traditional rigid docking algorithms, like PIPER, which often neglect critical stochastic elements such as solvent-induced fluctuations. These oversights...
2.
DiMucci D, Kon M, Segre D
Front Mol Biosci
. 2021 Jul;
8:663532.
PMID: 34222331
Machine learning is helping the interpretation of biological complexity by enabling the inference and classification of cellular, organismal and ecological phenotypes based on large datasets, e.g., from genomic, transcriptomic and...
3.
Cox J, Sherva R, Lunetta K, Saitz R, Kon M, Kranzler H, et al.
Explor Med
. 2021 Feb;
1(1):27-41.
PMID: 33554217
Aim: Racial disparities in opioid use disorder (OUD) management exist, however, and there is limited research on factors that influence opioid cessation in different population groups. Methods: We employed multiple...
4.
Castrillon-Candas J, Kon M
Adv Comput Math
. 2020 May;
46(3).
PMID: 32377059
In this paper we introduce concepts from uncertainty quantification (UQ) and numerical analysis for the efficient evaluation of stochastic high dimensional Newton iterates. In particular, we develop complex analytic regularity...
5.
DiMucci D, Kon M, Segre D
mSystems
. 2018 Nov;
3(5).
PMID: 30417106
Microbes affect each other's growth in multiple, often elusive, ways. The ensuing interdependencies form complex networks, believed to reflect taxonomic composition as well as community-level functional properties and dynamics. The...
6.
Mu X, Remiszewski S, Kon M, Ergin A, Diem M
Analyst
. 2018 Nov;
143(24):5935-5939.
PMID: 30406772
This paper reviews methods to arrive at optimum decision tree or label tree structures to analyze large SHP datasets. Supervised methods of analysis can utilize either sequential or (flat) multi-classifiers...
7.
Przybyszewski A, Kon M, Szlufik S, Szymanski A, Habela P, Koziorowski D
Sensors (Basel)
. 2016 Sep;
16(9).
PMID: 27649187
We still do not know how the brain and its computations are affected by nerve cell deaths and their compensatory learning processes, as these develop in neurodegenerative diseases (ND). Compensatory...
8.
Kim S, Kon M, Kang H
Biomed Res Int
. 2015 May;
2015:467514.
PMID: 25949998
New data sources for the analysis of cancer data are rapidly supplementing the large number of gene-expression markers used for current methods of analysis. Significant among these new sources are...
9.
Mu X, Kon M, Ergin A, Remiszewski S, Akalin A, Thompson C, et al.
Analyst
. 2015 Feb;
140(7):2449-64.
PMID: 25664623
We report results on a statistical analysis of an infrared spectral dataset comprising a total of 388 lung biopsies from 374 patients. The method of correlating classical and spectral results...
10.
Kim S, Park T, Kon M
Artif Intell Med
. 2014 Jul;
62(1):23-31.
PMID: 24997860
Objective: Although numerous studies related to cancer survival have been published, increasing the prediction accuracy of survival classes still remains a challenge. Integration of different data sets, such as microRNA...