Lukasz A. Kurgan

Orcid: 0000-0002-7749-0314

Affiliations:
  • Virginia Commonwealth University, Richmond, VA, USA
  • University of Alberta, Edmonton, Canada (former)


According to our database1, Lukasz A. Kurgan authored at least 97 papers between 2001 and 2023.

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Bibliography

2023
<i>ProsperousPlus</i>: a one-stop and comprehensive platform for accurate protease-specific substrate cleavage prediction and machine-learning model construction.
Briefings Bioinform., September, 2023

CAID prediction portal: a comprehensive service for predicting intrinsic disorder and binding regions in proteins.
Nucleic Acids Res., July, 2023

DEPICTER2: a comprehensive webserver for intrinsic disorder and disorder function prediction.
Nucleic Acids Res., July, 2023

A comprehensive assessment and comparison of tools for HLA class I peptide-binding prediction.
Briefings Bioinform., May, 2023

CLIP: accurate prediction of disordered linear interacting peptides from protein sequences using co-evolutionary information.
Briefings Bioinform., January, 2023

2022
<i>iFeatureOmega: </i> an integrative platform for engineering, visualization and analysis of features from molecular sequences, structural and ligand data sets.
Nucleic Acids Res., 2022

Guest editorial: Deep neural networks for precision medicine.
Neurocomputing, 2022

DeepDISOBind: accurate prediction of RNA-, DNA- and protein-binding intrinsically disordered residues with deep multi-task learning.
Briefings Bioinform., 2022

2021
DescribePROT: database of amino acid-level protein structure and function predictions.
Nucleic Acids Res., 2021

DisoLipPred: accurate prediction of disordered lipid-binding residues in protein sequences with deep recurrent networks and transfer learning.
Bioinform., 2021

XRRpred: accurate predictor of crystal structure quality from protein sequence.
Bioinform., 2021

Systematic evaluation of machine learning methods for identifying human-pathogen protein-protein interactions.
Briefings Bioinform., 2021

DNAgenie: accurate prediction of DNA-type-specific binding residues in protein sequences.
Briefings Bioinform., 2021

2020
Prediction of DNA-Binding Residues in Local Segments of Protein Sequences with Fuzzy Cognitive Maps.
IEEE ACM Trans. Comput. Biol. Bioinform., 2020

Attention convolutional neural network for accurate segmentation and quantification of lesions in ischemic stroke disease.
Medical Image Anal., 2020

Prediction of protein-binding residues: dichotomy of sequence-based methods developed using structured complexes versus disordered proteins.
Bioinform., 2020

DeepCleave: a deep learning predictor for caspase and matrix metalloprotease substrates and cleavage sites.
Bioinform., 2020

Corrigendum to: Comprehensive review and empirical analysis of hallmarks of DNA-, RNA- and protein-binding residues in protein chains.
Briefings Bioinform., 2020

Accuracy of protein-level disorder predictions.
Briefings Bioinform., 2020

Session Introduction.
Proceedings of the Pacific Symposium on Biocomputing 2020, 2020

Disordered Function Conjunction: On the In-Silico Function Annotation of Intrinsically DisorderedRegions.
Proceedings of the Pacific Symposium on Biocomputing 2020, 2020

2019
SCRIBER: accurate and partner type-specific prediction of protein-binding residues from proteins sequences.
Bioinform., 2019

Quality assessment for the putative intrinsic disorder in proteins.
Bioinform., 2019

Comprehensive review and empirical analysis of hallmarks of DNA-, RNA- and protein-binding residues in protein chains.
Briefings Bioinform., 2019

Review and comparative assessment of similarity-based methods for prediction of drug-protein interactions in the druggable human proteome.
Briefings Bioinform., 2019

2018
Review and comparative assessment of sequence-based predictors of protein-binding residues.
Briefings Bioinform., 2018

Critical evaluation of bioinformatics tools for the prediction of protein crystallization propensity.
Briefings Bioinform., 2018

2017
fDETECT webserver: fast predictor of propensity for protein production, purification, and crystallization.
BMC Bioinform., 2017

Exploratory Analysis of Quality Assessment of Putative Intrinsic Disorder in Proteins.
Proceedings of the Artificial Intelligence and Soft Computing, 2017

2016
PDID: database of molecular-level putative protein-drug interactions in the structural human proteome.
Bioinform., 2016

DFLpred: High-throughput prediction of disordered flexible linker regions in protein sequences.
Bioinform., 2016

A comprehensive comparative review of sequence-based predictors of DNA- and RNA-binding residues.
Briefings Bioinform., 2016

2015
Systematic investigation of sequence and structural motifs that recognize ATP.
Comput. Biol. Chem., 2015

Comprehensive overview and assessment of computational prediction of microRNA targets in animals.
Briefings Bioinform., 2015

Consensus-Based Prediction of RNA and DNA Binding Residues from Protein Sequences.
Proceedings of the Pattern Recognition and Machine Intelligence, 2015

2014
Sequence-based Gaussian network model for protein dynamics.
Bioinform., 2014

Human structural proteome-wide characterization of Cyclosporine A targets.
Bioinform., 2014

2013
mi-DS: Multiple-Instance Learning Algorithm.
IEEE Trans. Cybern., 2013

D<sup>2</sup>P<sup>2</sup>: database of disordered protein predictions.
Nucleic Acids Res., 2013

2012
Neural Networks in Bioinformatics.
Proceedings of the Handbook of Natural Computing, 2012

Learning of Fuzzy Cognitive Maps Using Density Estimate.
IEEE Trans. Syst. Man Cybern. Part B, 2012

SPINE X: Improving protein secondary structure prediction by multistep learning coupled with prediction of solvent accessible surface area and backbone torsion angles.
J. Comput. Chem., 2012

MoRFpred, a computational tool for sequence-based prediction and characterization of short disorder-to-order transitioning binding regions in proteins.
Bioinform., 2012

Prediction and analysis of nucleotide-binding residues using sequence and sequence-derived structural descriptors.
Bioinform., 2012

On the Complementarity of the Consensus-Based Disorder Prediction.
Proceedings of the Biocomputing 2012: Proceedings of the Pacific Symposium, 2012

2011
Improved Sequence-Based Prediction of Strand residues.
J. Bioinform. Comput. Biol., 2011

In-silico prediction of disorder content using hybrid sequence representation.
BMC Bioinform., 2011

Sequence-based prediction of protein crystallization, purification and production propensity.
Bioinform., 2011

Critical assessment of high-throughput standalone methods for secondary structure prediction.
Briefings Bioinform., 2011

2010
Machine Learning Algorithms Inspired by the Work of Ryszard Spencer Michalski.
Proceedings of the Advances in Machine Learning I: Dedicated to the Memory of Professor Ryszard S. Michalski, 2010

Recognition of Partially Occluded and Rotated Images With a Network of Spiking Neurons.
IEEE Trans. Neural Networks, 2010

Discovery of factors influencing patent value based on machine learning in patents in the field of nanotechnology.
Scientometrics, 2010

Discretization as the enabling technique for the Naïve Bayes and semi-Naïve Bayes-based classification.
Knowl. Eng. Rev., 2010

A divide and conquer method for learning large Fuzzy Cognitive Maps.
Fuzzy Sets Syst., 2010

Improved sequence-based prediction of disordered regions with multilayer fusion of multiple information sources.
Bioinform., 2010

Accurate prediction of ATP-binding residues using sequence and sequence-derived structural descriptors.
Proceedings of the 2010 IEEE International Conference on Bioinformatics and Biomedicine, 2010

2009
Prediction of protein folding rates from primary sequences using hybrid sequence representation.
J. Comput. Chem., 2009

Prediction of integral membrane protein type by collocated hydrophobic amino acid pairs.
J. Comput. Chem., 2009

Modular prediction of protein structural classes from sequences of twilight-zone identity with predicting sequences.
BMC Bioinform., 2009

2008
Numerical and Linguistic Prediction of Time Series With the Use of Fuzzy Cognitive Maps.
IEEE Trans. Fuzzy Syst., 2008

Impact of imputation of missing values on classification error for discrete data.
Pattern Recognit., 2008

Prediction of protein structural class using novel evolutionary collocation-based sequence representation.
J. Comput. Chem., 2008

A tree-projection-based algorithm for multi-label recurrent-item associative-classification rule generation.
Data Knowl. Eng., 2008

Prediction of beta-turns at over 80% accuracy based on an ensemble of predicted secondary structures and multiple alignments.
BMC Bioinform., 2008

Sequence based residue depth prediction using evolutionary information and predicted secondary structure.
BMC Bioinform., 2008

SCPRED: Accurate prediction of protein structural class for sequences of twilight-zone similarity with predicting sequences.
BMC Bioinform., 2008

Improved machine learning method for analysis of gas phase chemistry of peptides.
BMC Bioinform., 2008

Accurate sequence-based prediction of catalytic residues.
Bioinform., 2008

HuMiTar: A sequence-based method for prediction of human microRNA targets.
Algorithms Mol. Biol., 2008

Use of OWL 2 to Facilitate a Biomedical Knowledge Base Extracted from the GENIA Corpus.
Proceedings of the Fifth OWLED Workshop on OWL: Experiences and Directions, 2008

Comparative Analysis of the Impact of Discretization on the Classification with Naïve Bayes and Semi-Naïve Bayes Classifiers.
Proceedings of the Seventh International Conference on Machine Learning and Applications, 2008

Data-driven Nonlinear Hebbian Learning method for Fuzzy Cognitive Maps.
Proceedings of the FUZZ-IEEE 2008, 2008

2007
A Novel Framework for Imputation of Missing Values in Databases.
IEEE Trans. Syst. Man Cybern. Part A, 2007

PFRES: protein fold classification by using evolutionary information and predicted secondary structure.
Bioinform., 2007

Parallel Learning of Large Fuzzy Cognitive Maps.
Proceedings of the International Joint Conference on Neural Networks, 2007

Classification of Cell Membrane Proteins.
Proceedings of the Frontiers in the Convergence of Bioscience and Information Technologies 2007, 2007

2006
Highly scalable and robust rule learner: performance evaluation and comparison.
IEEE Trans. Syst. Man Cybern. Part B, 2006

A new synaptic plasticity rule for networks of spiking neurons.
IEEE Trans. Neural Networks, 2006

Prediction of structural classes for protein sequences and domains - Impact of prediction algorithms, sequence representation and homology, and test procedures on accuracy.
Pattern Recognit., 2006

A survey of Knowledge Discovery and Data Mining process models.
Knowl. Eng. Rev., 2006

A comment on "Prediction of protein structural classes by a new measure of information discrepancy".
Comput. Biol. Chem., 2006

Impact of the Predicted Protein Structural Content on Prediction of Structural Classes for the Twilight Zone Proteins.
Proceedings of the Fifth International Conference on Machine Learning and Applications, 2006

Prediction of the Number of Helices for the Twilight Zone Proteins.
Proceedings of the 2006 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, 2006

Optimization of the Sliding Window Size for Protein Structure Prediction.
Proceedings of the 2006 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, 2006

2005
Genetic learning of fuzzy cognitive maps.
Fuzzy Sets Syst., 2005

Highly accurate and consistent method for prediction of helix and strand content from primary protein sequences.
Artif. Intell. Medicine, 2005

Prediction of Secondary Protein Structure Content from Primary Sequence Alone - A Feature Selection Based Approach.
Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2005

Multi-label associative classification of medical documents from MEDLINE.
Proceedings of the Fourth International Conference on Machine Learning and Applications, 2005

Evolutionary Development of Fuzzy Cognitive Maps.
Proceedings of the IEEE International Conference on Fuzzy Systems, 2005

2004
CAIM Discretization Algorithm.
IEEE Trans. Knowl. Data Eng., 2004

CLIP4: Hybrid inductive machine learning algorithm that generates inequality rules.
Inf. Sci., 2004

Reducing complexity of rule based models via meta mining.
Proceedings of the 2004 International Conference on Machine Learning and Applications, 2004

2003
Fast Class-Attribute Interdependence Maximization (CAIM) Discretization Algorithm.
Proceedings of the 2003 International Conference on Machine Learning and Applications, 2003

2002
Semantic Mapping of XML Tags Using Inductive Machine Learning.
Proceedings of the 2002 International Conference on Machine Learning and Applications, 2002

2001
SPECTF Heart.
Dataset, September, 2001

SPECT Heart.
Dataset, September, 2001

Knowledge discovery approach to automated cardiac SPECT diagnosis.
Artif. Intell. Medicine, 2001


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