A new phylogenetic diversity measure generalizing the Shannon index and its application to phyllostomid bats B Allen, M Kon, Y Bar-Yam The American Naturalist 174 (2), 236-243, 2009 | 215 | 2009 |
Infrared spectral histopathology (SHP): a novel diagnostic tool for the accurate classification of lung cancer B Bird, M Miljković, S Remiszewski, A Akalin, M Kon, M Diem Laboratory investigation 92 (9), 1358-1373, 2012 | 153 | 2012 |
Local convergence for wavelet expansions SE Kelly, MA Kon, LA Raphael Journal of Functional Analysis 126 (1), 102-138, 1994 | 141 | 1994 |
Pointwise convergence of wavelet expansions SE Kelly, MA Kon, LA Raphael Bulletin of The American Mathematical Society 30 (1), 87-94, 1994 | 139 | 1994 |
Pathway-based classification of cancer subtypes S Kim, M Kon, C DeLisi Biology direct 7, 1-22, 2012 | 126 | 2012 |
Exact smoothing properties of Schrödinger semigroups A Gulisashvili, MA Kon American Journal of Mathematics 118 (6), 1215-1248, 1996 | 125 | 1996 |
Oscillation criteria for delay equations M Kon, Y Sficas, I Stavroulakis Proceedings of the American Mathematical Society 128 (10), 2989-2997, 2000 | 94 | 2000 |
Biomedical Informatics for Computer‐Aided Decision Support Systems: A Survey A Belle, MA Kon, K Najarian The Scientific World Journal 2013 (1), 769639, 2013 | 90 | 2013 |
Top scoring pairs for feature selection in machine learning and applications to cancer outcome prediction P Shi, S Ray, Q Zhu, MA Kon BMC bioinformatics 12, 1-15, 2011 | 76 | 2011 |
Integrating genomic data to predict transcription factor binding DT Holloway, M Kon, C De Lisi Genome informatics 16 (1), 83-94, 2005 | 73 | 2005 |
Lecture Notes in Mathematics MA Kon | 73* | |
Classification of malignant and benign tumors of the lung by infrared spectral histopathology (SHP) A Akalin, X Mu, MA Kon, A Ergin, SH Remiszewski, CM Thompson, ... Laboratory investigation 95 (4), 406-421, 2015 | 72 | 2015 |
Methods and systems for classifying biological samples, including optimization of analyses and use of correlation SH Remiszewski, M Diem, CM Thompson, A Ergin, MU Xinying, ... US Patent 10,043,054, 2018 | 70 | 2018 |
Information complexity of neural networks MA Kon, L Plaskota Neural Networks 13 (3), 365-375, 2000 | 59 | 2000 |
Machine learning reveals missing edges and putative interaction mechanisms in microbial ecosystem networks D DiMucci, M Kon, D Segrè Msystems 3 (5), 10.1128/msystems. 00181-18, 2018 | 53 | 2018 |
Algorithms and complexity JF Traub Academic, 1976 | 48 | 1976 |
Multimodal learning and intelligent prediction of symptom development in individual Parkinson’s patients AW Przybyszewski, M Kon, S Szlufik, A Szymanski, P Habela, ... Sensors 16 (9), 1498, 2016 | 41 | 2016 |
Information-based nonlinear approximation: an average case setting M Kon, L Plaskota Journal of Complexity 21 (2), 211-229, 2005 | 36 | 2005 |
Machine learning for regulatory analysis and transcription factor target prediction in yeast DT Holloway, M Kon, C DeLisi Systems and synthetic biology 1, 25-46, 2007 | 34 | 2007 |
Statistical analysis of a lung cancer spectral histopathology (SHP) data set X Mu, M Kon, A Ergin, S Remiszewski, A Akalin, CM Thompson, M Diem Analyst 140 (7), 2449-2464, 2015 | 33 | 2015 |