Lukasz A. Kurgan
Orcid: 0000-0002-7749-0314Affiliations:
- 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.
Collaborative distances:
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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
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
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
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
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
Comput. Biol. Chem., 2015
Comprehensive overview and assessment of computational prediction of microRNA targets in animals.
Briefings Bioinform., 2015
Proceedings of the Pattern Recognition and Machine Intelligence, 2015
2014
Bioinform., 2014
2013
Nucleic Acids Res., 2013
2012
Proceedings of the Handbook of Natural Computing, 2012
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
Proceedings of the Biocomputing 2012: Proceedings of the Pacific Symposium, 2012
2011
J. Bioinform. Comput. Biol., 2011
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
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
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
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
BMC Bioinform., 2008
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
Proceedings of the FUZZ-IEEE 2008, 2008
2007
IEEE Trans. Syst. Man Cybern. Part A, 2007
PFRES: protein fold classification by using evolutionary information and predicted secondary structure.
Bioinform., 2007
Proceedings of the International Joint Conference on Neural Networks, 2007
Proceedings of the Frontiers in the Convergence of Bioscience and Information Technologies 2007, 2007
2006
IEEE Trans. Syst. Man Cybern. Part B, 2006
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
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
Proceedings of the 2006 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, 2006
Proceedings of the 2006 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, 2006
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
Proceedings of the Fourth International Conference on Machine Learning and Applications, 2005
Proceedings of the IEEE International Conference on Fuzzy Systems, 2005
2004
Inf. Sci., 2004
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
Artif. Intell. Medicine, 2001