| Guidelines for the use and interpretation of assays for monitoring autophagy DJ Klionsky, AK Abdel-Aziz, S Abdelfatah, M Abdellatif, A Abdoli, S Abel, ... autophagy 17 (1), 1-382, 2021 | 11309 | 2021 |
| 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 | 747 | 2012 |
| A survey of knowledge discovery and data mining process models LA Kurgan, P Musilek The Knowledge Engineering Review 21 (1), 1-24, 2006 | 655 | 2006 |
| CAIM discretization algorithm LA Kurgan, KJ Cios IEEE transactions on Knowledge and Data Engineering 16 (2), 145-153, 2004 | 646 | 2004 |
| Genetic learning of fuzzy cognitive maps W Stach, L Kurgan, W Pedrycz, M Reformat Fuzzy sets and systems 153 (3), 371-401, 2005 | 623 | 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 | 476 | 2008 |
| 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, 137-151, 2015 | 413 | 2015 |
| 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 | 381 | 2012 |
| 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 | 337 | 2001 |
| 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 | 325 | 2007 |
| 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 | 304 | 2012 |
| Critical assessment of protein intrinsic disorder prediction M Necci, D Piovesan, SCE Tosatto Nature methods 18 (5), 472-481, 2021 | 274 | 2021 |
| Trends in data mining and knowledge discovery KJ Cios, LA Kurgan Advanced techniques in knowledge discovery and data mining, 1-26, 2005 | 231 | 2005 |
| flDPnn: Accurate intrinsic disorder prediction with putative propensities of disorder functions G Hu, A Katuwawala, K Wang, Z Wu, S Ghadermarzi, J Gao, L Kurgan Nature communications 12 (1), 4438, 2021 | 226 | 2021 |
| DRNApred, fast sequence-based method that accurately predicts and discriminates DNA-and RNA-binding residues J Yan, L Kurgan Nucleic acids research 45 (10), e84-e84, 2017 | 224 | 2017 |
| Structural disorder in viral proteins B Xue, D Blocquel, J Habchi, AV Uversky, L Kurgan, VN Uversky, ... Chemical reviews 114 (13), 6880-6911, 2014 | 219 | 2014 |
| 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 | 206 | 2010 |
| 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 | 203 | 2006 |
| 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 | 202 | 2008 |
| 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 | 198 | 2006 |
Vladimir UverskyProfessor, USFVerified email at usf.edu
