Lukasz Kurgan
Cited by
Cited by
Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1
DJ Klionsky, AK Abdel-Aziz, S Abdelfatah, M Abdellatif, A Abdoli, S Abel, ...
autophagy 17 (1), 1-382, 2021
CAIM discretization algorithm
LA Kurgan, KJ Cios
IEEE transactions on Knowledge and Data Engineering 16 (2), 145-153, 2004
A survey of knowledge discovery and data mining process models
LA Kurgan, P Musilek
The Knowledge Engineering Review 21 (1), 1-24, 2006
D2P2: database of disordered protein predictions
ME Oates, P Romero, T Ishida, M Ghalwash, MJ Mizianty, B Xue, ...
Nucleic acids research 41 (D1), D508-D516, 2012
Genetic learning of fuzzy cognitive maps
W Stach, L Kurgan, W Pedrycz, M Reformat
Fuzzy sets and systems 153 (3), 371-401, 2005
Impact of imputation of missing values on classification error for discrete data
A Farhangfar, L Kurgan, J Dy
Pattern Recognition 41 (12), 3692-3705, 2008
MoRFpred, a computational tool for sequence-based prediction and characterization of short disorder-to-order transitioning binding regions in proteins
FM Disfani, WL Hsu, MJ Mizianty, CJ Oldfield, B Xue, AK Dunker, ...
Bioinformatics 28 (12), i75-i83, 2012
Exceptionally abundant exceptions: comprehensive characterization of intrinsic disorder in all domains of life
Z Peng, J Yan, X Fan, MJ Mizianty, B Xue, K Wang, G Hu, VN Uversky, ...
Cellular and Molecular Life Sciences 72 (1), 137-151, 2015
Knowledge discovery approach to automated cardiac SPECT diagnosis
LA Kurgan, KJ Cios, R Tadeusiewicz, M Ogiela, LS Goodenday
Artificial intelligence in medicine 23 (2), 149-169, 2001
SPINE X: improving protein secondary structure prediction by multistep learning coupled with prediction of solvent accessible surface area and backbone torsion angles
E Faraggi, T Zhang, Y Yang, L Kurgan, Y Zhou
Journal of computational chemistry 33 (3), 259-267, 2012
A novel framework for imputation of missing values in databases
A Farhangfar, LA Kurgan, W Pedrycz
IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and …, 2007
Trends in data mining and knowledge discovery
KJ Cios, LA Kurgan
Advanced techniques in knowledge discovery and data mining, 1-26, 2005
Classifier ensembles for protein structural class prediction with varying homology
KD Kedarisetti, L Kurgan, S Dick
Biochemical and Biophysical Research Communications 348 (3), 981-988, 2006
Prediction of structural classes for protein sequences and domains—impact of prediction algorithms, sequence representation and homology, and test procedures on accuracy
LA Kurgan, L Homaeian
Pattern Recognition 39 (12), 2323-2343, 2006
Improved sequence-based prediction of disordered regions with multilayer fusion of multiple information sources
MJ Mizianty, W Stach, K Chen, KD Kedarisetti, FM Disfani, L Kurgan
Bioinformatics 26 (18), i489-i496, 2010
Prediction of protein structural class using novel evolutionary collocation‐based sequence representation
KE Chen, LA Kurgan, J Ruan
Journal of computational chemistry 29 (10), 1596-1604, 2008
Comprehensive comparative assessment of in-silico predictors of disordered regions
ZL Peng, L Kurgan
Current Protein and Peptide Science 13 (1), 6-18, 2012
Structural disorder in viral proteins
B Xue, D Blocquel, J Habchi, AV Uversky, L Kurgan, VN Uversky, ...
Chemical reviews 114 (13), 6880-6911, 2014
Numerical and linguistic prediction of time series with the use of fuzzy cognitive maps
W Stach, LA Kurgan, W Pedrycz
IEEE transactions on fuzzy systems 16 (1), 61-72, 2008
SCPRED: accurate prediction of protein structural class for sequences of twilight-zone similarity with predicting sequences
L Kurgan, K Cios, K Chen
BMC bioinformatics 9 (1), 1-15, 2008
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