Lukasz Kurgan

发表

Comprehensive Survey and Comparative Assessment of RNA-Binding Residue Predictions with Analysis by RNA Type

Kui Wang, Gang Hu, Zhonghua Wu, 2020, International journal of molecular sciences.

Prediction of DNA-Binding Residues in Local Segments of Protein Sequences with Fuzzy Cognitive Maps

Lukasz Kurgan, Mojtaba Kolahdoozi, Abdollah Amirkhani, 2020, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Computational Prediction of Secondary and Supersecondary Structures from Protein Sequences.

Lukasz Kurgan, Christopher J Oldfield, Ke Chen, 2019, Methods in molecular biology.

DeepCleave: a deep learning predictor for caspase and matrix metalloprotease substrates and cleavage sites

Geoffrey I. Webb, Jiangning Song, Tatsuya Akutsu, 2019, Bioinform..

Fourth International Conference on Machine Learning and Applications, ICMLA 2005, Los Angeles, California, USA, 15-17 December 2005

Lukasz Kurgan, M. Arif Wani, Khalid Hafeez, 2005, ICMLA.

Comprehensively designed consensus of standalone secondary structure predictors improves Q3 by over 3%

Lukasz Kurgan, Jing Yan, Max Marcus, 2014, Journal of biomolecular structure & dynamics.

Meta mining system for supervised learning

Lukasz Kurgan, Krzysztof J. Cios, K. Cios, 2003 .

The Knowledge Discovery Process

Witold Pedrycz, Witold Pedrycz, Lukasz Kurgan, 2007 .

Attention convolutional neural network for accurate segmentation and quantification of lesions in ischemic stroke disease

Lukasz Kurgan, Jianxin Wang, Fang-Xiang Wu, 2020, Medical Image Anal..

The Methods and Tools for Intrinsic Disorder Prediction and their Application to Systems Medicine

Lukasz Kurgan, Min Li, Yaohang Li, 2021 .

Ensemble of classifiers to improve accuracy of the CLIP4 machine-learning algorithm

Lukasz Kurgan, Krzysztof J. Cios, K. Cios, 2002, SPIE Defense + Commercial Sensing.

Computational Prediction of Intrinsic Disorder in Proteins

Lukasz Kurgan, Fanchi Meng, Vladimir Uversky, 2017, Current protocols in protein science.

Prediction of intrinsic disorder in proteins using MFDp2.

Lukasz Kurgan, Marcin J Mizianty, Vladimir Uversky, 2014, Methods in molecular biology.

Databases, Data Warehouses, and OLAP

Witold Pedrycz, Lukasz Kurgan, Roman W. Swiniarski, 2007 .

Concepts of Learning, Classification, and Regression

Witold Pedrycz, Lukasz Kurgan, Roman W. Swiniarski, 2007 .

NetEPD: A network-based essential protein discovery platform

Lukasz Kurgan, Wenkai Li, Min Zeng, 2020 .

xGENIA: A comprehensive OWL ontology based on the GENIA corpus

Lukasz Kurgan, Marek Reformat, Rafal Rak, 2007, Bioinformation.

Data Mining: A Knowledge Discovery Approach

Witold Pedrycz, Lukasz Kurgan, Krzysztof J. Cios, 2007 .

DeepFunc: A Deep Learning Framework for Accurate Prediction of Protein Functions from Protein Sequences and Interactions

Yaohang Li, Hong Song, Lukasz Kurgan, 2019, Proteomics.

Assessment of Data Models

Witold Pedrycz, Lukasz Kurgan, Roman W. Swiniarski, 2007 .

Review and comparative assessment of similarity-based methods for prediction of drug-protein interactions in the druggable human proteome

Lukasz Kurgan, Chen Wang, Lukasz Kurgan, 2018, Briefings Bioinform..

DeepCNF-D: Predicting Protein Order/Disorder Regions by Weighted Deep Convolutional Neural Fields

Lukasz Kurgan, Jianzhu Ma, Sheng Wang, 2015, International journal of molecular sciences.

Disordered RNA-Binding Region Prediction with DisoRDPbind.

Lukasz Kurgan, Christopher J Oldfield, Zhenling Peng, 2020, Methods in molecular biology.

Sequence Similarity Searching

Lukasz Kurgan, Gang Hu, Lukasz Kurgan, 2018, Current protocols in protein science.

Computational prediction of secondary and supersecondary structures.

Lukasz Kurgan, Ke Chen, Ke Chen, 2013, Methods in molecular biology.

The Sixth International Conference on Machine Learning and Applications, ICMLA 2007, Cincinnati, Ohio, USA, 13-15 December 2007

Jieping Ye, Seref Sagiroglu, Lukasz Kurgan, 2008, ICMLA.

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

Lukasz Kurgan, Zhiqiang Ma, Jian Zhang, 2019, Briefings Bioinform..

Disordered Function Conjunction: On the In-Silico Function Annotation of Intrinsically DisorderedRegions

Lukasz Kurgan, Christopher J. Oldfield, Sina Ghadermarzi, 2019, PSB.

Human structural proteome-wide characterization of Cyclosporine A targets

Kui Wang, Lukasz Kurgan, Gang Hu, 2014, Bioinform..

Predicting Functions of Disordered Proteins with MoRFpred.

Lukasz Kurgan, Christopher J Oldfield, Christopher J. Oldfield, 2018, Methods in molecular biology.

Ensemble of Classifiers Ensemble of Classifiers to Improve Accuracy of to Improve Accuracy of SPECT Heart Image Analysis System SPECT Heart Image Analysis System

Lukasz Kurgan, 2002 .

Lukasz Kurgan, Chen Wang, Lukasz Kurgan, 2018, Current medicinal chemistry.

Prediction of Ion Channels and their Types from Protein Sequences: Comprehensive Review and Comparative Assessment.

Lukasz Kurgan, Jianzhao Gao, Hong Wei, 2019, Current drug targets.

Supervised Learning: Decision Trees, Rule Algorithms, and Their Hybrids

Witold Pedrycz, Lukasz Kurgan, Roman W. Swiniarski, 2007 .

Systematic evaluation of machine learning methods for identifying human-pathogen protein-protein interactions

Jiangning Song, Lei Wang, Lukasz Kurgan, 2020, Briefings Bioinform..

Accurate prediction of disorder in protein chains with a comprehensive and empirically designed consensus

Lukasz Kurgan, Xiao Fan, Lukasz Kurgan, 2014, Journal of biomolecular structure & dynamics.

Supplement for article entitled "MoRFpred, a computational tool for sequence-based prediction and characterization of short disorder-to-order transitioning bind- ing regions in proteins"

Lukasz Kurgan, Vladimir N. Uversky, Christopher J. Oldfield, 2005 .

Computational prediction of functions of intrinsically disordered regions.

Lukasz Kurgan, Sina Ghadermarzi, Akila Katuwawala, 2019, Progress in molecular biology and translational science.

Computational Prediction of Intrinsic Disorder in Protein Sequences with the disCoP Meta-predictor.

A Keith Dunker, Lukasz Kurgan, Christopher J Oldfield, 2020, Methods in molecular biology.

The Fifth International Conference on Machine Learning and Applications, ICMLA 2006, Orlando, Florida, USA, 14-16 December 2006

Jieping Ye, Lukasz Kurgan, Ying Liu, 2006, ICMLA.

Feature Extraction and Selection Methods

Witold Pedrycz, Witold Pedrycz, Lukasz Kurgan, 2007 .

Trends in Data Mining and Knowledge Discovery

Lukasz Kurgan, Krzysztof J. Cios, K. Cios, 2005 .

Mining the Cystic Fibrosis Data

Lukasz Kurgan, Krzysztof J. Cios, Marci K. Sontag, 2005 .

PSIONplusm Server for Accurate Multi-Label Prediction of Ion Channels and Their Types

Lukasz Kurgan, Alberto Cano, Hong Wei, 2020, Biomolecules.

Comprehensive comparative assessment of in-silico predictors of disordered regions.

Lukasz Kurgan, Zhen-Ling Peng, Lukasz Kurgan, 2012, Current protein & peptide science.

Computational Prediction of Protein Secondary Structure from Sequence

Lukasz Kurgan, Fanchi Meng, Lukasz Kurgan, 2016, Current protocols in protein science.

Learning fuzzy cognitive maps with required precision using genetic algorithm approach

Witold Pedrycz, Lukasz Kurgan, Marek Reformat, 2004 .

Unsupervised Learning: Association Rules

Witold Pedrycz, Lukasz Kurgan, Roman W. Swiniarski, 2007 .

Accuracy of protein-level disorder predictions

Lukasz Kurgan, Christopher J Oldfield, Christopher J. Oldfield, 2020, Briefings Bioinform..

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

Lukasz Kurgan, Jian Zhang, Lukasz Kurgan, 2019, Bioinform..

Seventh International Conference on Machine Learning and Applications, ICMLA 2008, San Diego, California, USA, 11-13 December 2008

Lukasz Kurgan, David Casasent, M. Arif Wani, 2008, ICMLA.

Discretization Algorithm that Uses Class-Attribute Interdependence Maximization

Lukasz Kurgan, Krzysztof J. Cios, K. Cios, 2003 .

DEPICTER: intrinsic disorder and disorder function prediction server.

Yaoqi Zhou, Lukasz Kurgan, Kuldip Paliwal, 2019, Journal of molecular biology.

Experimental analysis of methods for imputation of missing values in databases

Witold Pedrycz, Lukasz Kurgan, Alireza Farhangfar, 2004, SPIE Defense + Commercial Sensing.

Proceedings - Seventh International Conference on Machine Learning and Applications, ICMLA 2008: Preface

Lukasz Kurgan, David Casasent, M. Arif Wani, 2006 .

Machine learning models in protein bioinformatics.

Yaoqi Zhou, Lukasz Kurgan, Yaoqi Zhou, 2011, Current protein & peptide science.

Expert-Based and Computational Methods for Developing Fuzzy Cognitive Maps

Witold Pedrycz, Lukasz Kurgan, Wojciech Stach, 2010 .

Unsupervised Learning: Clustering

Witold Pedrycz, Lukasz Kurgan, Roman W. Swiniarski, 2007 .

Survey of Predictors of Propensity for Protein Production and Crystallization with Application to Predict Resolution of Crystal Structures.

Jiangning Song, Kui Wang, Zhonghua Wu, 2017, Current protein & peptide science.

Computational prediction of B cell epitopes from antigen sequences.

Lukasz Kurgan, Jianzhao Gao, Lukasz Kurgan, 2014, Methods in molecular biology.

Prediction of Intrinsic Disorder with Quality Assessment Using QUARTER.

Gang Hu, Zhonghua Wu, Lukasz Kurgan, 2020, Methods in molecular biology.

Data Security, Privacy and Data Mining

Witold Pedrycz, Lukasz Kurgan, Roman W. Swiniarski, 2007 .

Supervised Learning: Neural Networks

Witold Pedrycz, Lukasz Kurgan, Roman W. Swiniarski, 2007 .

iFC2: an integrated web-server for improved prediction of protein structural class, fold type, and secondary structure content

Lukasz Kurgan, Ke Chen, Leila Homaeian, 2010, Amino Acids.

International Conference on Machine Learning and Applications, ICMLA 2009, Miami Beach, Florida, USA, December 13-15, 2009

Lukasz Kurgan, M. Arif Wani, Vasile Palade, 2009, ICMLA.

Supervised Learning: Statistical Methods

Witold Pedrycz, Lukasz Kurgan, Roman W. Swiniarski, 2007 .

PSIONplus: Accurate Sequence-Based Predictor of Ion Channels and Their Types

Lukasz Kurgan, Jianzhao Gao, Jishou Ruan, 2016, PloS one.

PDID: Database of Experimental and Putative Drug Targets in Human Proteome

Lukasz Kurgan, Michal Brylinski, Chen Wang, 2019, In Silico Drug Design.

BEST: Improved Prediction of B-Cell Epitopes from Antigen Sequences

Yaoqi Zhou, Lukasz Kurgan, Jianzhao Gao, 2012, PloS one.

A Framework for a Novel Scalable FCM Learning Method

Witold Pedrycz, Lukasz Kurgan, Wojciech Stach, 2007 .

Data Mining and Knowledge Discovery Data Mining and Knowledge Discovery

Lukasz Kurgan, Lukasz Kurgan, 2002 .

Accurate prediction of protein folding rates from sequence and sequence‐derived residue flexibility and solvent accessibility

Lukasz Kurgan, Jianzhao Gao, Hua Zhang, 2010, Proteins.

Systematic investigation of sequence and structural motifs that recognize ATP

Ke Chen, Lukasz Kurgan, Dacheng Wang, 2015, Comput. Biol. Chem..

High‐throughput prediction of disordered moonlighting regions in protein sequences

Lukasz Kurgan, Fanchi Meng, Lukasz Kurgan, 2018, Proteins.

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

Lukasz Kurgan, Jian Zhang, Sina Ghadermarzi, 2020, Bioinform..

Genetic learning offuzzy cognitive maps

Lukasz Kurgan, W. Pedrycz, Marek Reformat, 2005 .

Structural protein descriptors in 1-dimension and their sequence-based predictions.

Lukasz Kurgan, Fatemeh Miri Disfani, Lukasz Kurgan, 2011, Current protein & peptide science.

Comparative Assessment of Intrinsic Disorder Predictions with a Focus on Protein and Nucleic Acid-Binding Proteins

Lukasz Kurgan, Akila Katuwawala, Lukasz Kurgan, 2020, Biomolecules.

DISOselect: Disorder predictor selection at the protein level

Lukasz Kurgan, Akila Katuwawala, Christopher Oldfield, 2020, Protein science : a publication of the Protein Society.

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

Lukasz Kurgan, Bi Zhao, Akila Katuwawala, 2021, Bioinform..

DNAgenie: accurate prediction of DNA-type-specific binding residues in protein sequences

Lukasz Kurgan, Sina Ghadermarzi, Akila Katuwawala, 2021, Briefings Bioinform..

XRRpred: accurate predictor of crystal structure quality from protein sequence

Lukasz Kurgan, Bartosz Krawczyk, Sina Ghadermarzi, 2021, Bioinform..

DescribePROT: database of amino acid-level protein structure and function predictions

A Keith Dunker, Zoran Obradovic, Lukasz Kurgan, 2020, Nucleic Acids Res..

In various protein complexes, disordered protomers have large per‐residue surface areas and area of protein‐, DNA‐ and RNA‐binding interfaces

Lukasz Kurgan, Jianyi Yang, Zhenling Peng, 2015, FEBS letters.

In Silico Prediction and Validation of Novel RNA Binding Proteins and Residues in the Human Proteome

Lukasz Kurgan, Jian Zhang, Shomeek Chowdhury, 2018, Proteomics.

On the relation between residue flexibility and local solvent accessibility in proteins

Lukasz Kurgan, Ke Chen, Shiyi Shen, 2009, Proteins.

Functional Analysis of Human Hub Proteins and Their Interactors Involved in the Intrinsic Disorder-Enriched Interactions

Lukasz Kurgan, Vladimir N Uversky, Lukasz Kurgan, 2017, International journal of molecular sciences.

Structural disorder in viral proteins.

Sonia Longhi, Lukasz Kurgan, Vladimir N Uversky, 2014, Chemical reviews.

Covering complete proteomes with X-ray structures: a current snapshot

Lukasz Kurgan, Jing Yan, Marcin J. Mizianty, 2014, Acta crystallographica. Section D, Biological crystallography.

Untapped Potential of Disordered Proteins in Current Druggable Human Proteome.

Lukasz Kurgan, Vladimir N Uversky, Lukasz Kurgan, 2016, Current drug targets.

ATPsite: sequence-based prediction of ATP-binding residues

Lukasz Kurgan, Ke Chen, Marcin J Mizianty, 2011, Proteome Science.

Meta prediction of protein crystallization propensity.

Lukasz Kurgan, Marcin J. Mizianty, Lukasz Kurgan, 2009, Biochemical and biophysical research communications.

Lukasz Kurgan, Vladimir N. Uversky, Fanchi Meng, 2016, Molecular bioSystems.

CRYSTALP2: sequence-based protein crystallization propensity prediction

Scott Dick, Lukasz Kurgan, Samad Jahandideh, 2009, BMC Structural Biology.

Prediction of Disordered RNA, DNA, and Protein Binding Regions Using DisoRDPbind.

Lukasz Kurgan, Zhenling Peng, Vladimir N Uversky, 2017, Methods in molecular biology.

A creature with a hundred waggly tails: intrinsically disordered proteins in the ribosome

Lukasz Kurgan, Zhenling Peng, A. Keith Dunker, 2013, Cellular and Molecular Life Sciences.

Intrinsic Disorder in the BK Channel and Its Interactome

Lukasz Kurgan, Zhenling Peng, Vladimir Uversky, 2014, PloS one.

Compartmentalization and Functionality of Nuclear Disorder: Intrinsic Disorder and Protein-Protein Interactions in Intra-Nuclear Compartments

Lukasz Kurgan, Vladimir N. Uversky, Fanchi Meng, 2015, International journal of molecular sciences.

What are the structural features that drive partitioning of proteins in aqueous two-phase systems?

Lukasz Kurgan, Vladimir N Uversky, Lukasz Kurgan, 2017, Biochimica et biophysica acta. Proteins and proteomics.

Sequence-Only Based Prediction of β -Turn Location and Type Using Collocation of Amino Acid Pairs

Lukasz Kurgan, Lukasz Kurgan, K. Campbell, 2008 .

Finding protein targets for small biologically relevant ligands across fold space using inverse ligand binding predictions.

Lukasz Kurgan, Jianzhao Gao, Jishou Ruan, 2012, Structure.

Sequence based prediction of relative solvent accessibility using two-stage support vector regression with confidence values

Lukasz Kurgan, Ke Chen, Ke Chen, 2008 .

Improved prediction of residue flexibility by embedding optimized amino acid grouping into RSA-based linear models

Lukasz Kurgan, Hua Zhang, Lukasz Kurgan, 2014, Amino Acids.

Identification of tubulin drug binding sites and prediction of relative differences in binding affinities to tubulin isotypes using digital signal processing.

Andreas Antoniou, Lukasz Kurgan, Ke Chen, 2008, Journal of molecular graphics & modelling.

Taxonomic Landscape of the Dark Proteomes: Whole‐Proteome Scale Interplay Between Structural Darkness, Intrinsic Disorder, and Crystallization Propensity

Jiangning Song, Lukasz Kurgan, Vladimir N Uversky, 2018, Proteomics.

Molecular recognition features (MoRFs) in three domains of life.

A Keith Dunker, Lukasz Kurgan, Jing Yan, 2016, Molecular bioSystems.

More than just tails: intrinsic disorder in histone proteins.

Lukasz Kurgan, Zhenling Peng, Marcin J Mizianty, 2012, Molecular bioSystems.

Sequence-Based Methods for Real Value Predictions of Protein Structure

Lukasz Kurgan, Krzysztof J. Cios, Ke Chen, 2008 .

Sequence-Based Protein Crystallization Propensity Prediction for Structural Genomics: Review and Comparative Analysis

Lukasz Kurgan, Marcin J. Mizianty, Lukasz Kurgan, 2009 .

High-throughput prediction of RNA, DNA and protein binding regions mediated by intrinsic disorder

Lukasz Kurgan, Zhenling Peng, Lukasz Kurgan, 2015, Nucleic acids research.

MFDp2: Accurate predictor of disorder in proteins by fusion of disorder probabilities, content and profiles.

Lukasz Kurgan, Zhenling Peng, Marcin J Mizianty, 2013, Intrinsically disordered proteins.

Determination of protein folding kinetic types using sequence and predicted secondary structure and solvent accessibility

Lukasz Kurgan, Jianzhao Gao, Shiyi Shen, 2010, Amino Acids.

Corrigendum: Critical evaluation of bioinformatics tools for the prediction of protein crystallization propensity [Briefings in Bioinformatics, (2017)] doi: 10.1093/bib/bbx018

Liubin Feng, Geoffrey I. Webb, Lukasz Kurgan, 2017 .

Classifier ensembles for protein structural class prediction with varying homology.

Scott Dick, Lukasz Kurgan, Kanaka Durga Kedarisetti, 2006, Biochemical and biophysical research communications.

Prediction of protein crystallization using collocation of amino acid pairs.

Lukasz Kurgan, Ke Chen, Mandana Rahbari, 2007, Biochemical and biophysical research communications.

Disordered nucleiome: Abundance of intrinsic disorder in the DNA‐ and RNA‐binding proteins in 1121 species from Eukaryota, Bacteria and Archaea

Lukasz Kurgan, Vladimir N Uversky, Lukasz Kurgan, 2016, Proteomics.

DRNApred, fast sequence-based method that accurately predicts and discriminates DNA- and RNA-binding residues

Lukasz Kurgan, Jing Yan, Lukasz Kurgan, 2017, Nucleic acids research.

Prediction of protein structural class for the twilight zone sequences.

Lukasz Kurgan, Ke Chen, Ke Chen, 2007, Biochemical and biophysical research communications.

The intrinsic disorder status of the human hepatitis C virus proteome.

Lukasz Kurgan, Vladimir N Uversky, Bin Xue, 2014, Molecular bioSystems.

Lukasz Kurgan, Lukasz Kurgan, Chen Wang, 2018, Current medicinal chemistry.

Battlecity Revived: Game Design with BDI.net

Lukasz Kurgan, Petr Musilek, Yifan Li, 2004 .

A critical comparative assessment of predictions of protein-binding sites for biologically relevant organic compounds.

Lukasz Kurgan, Jianzhao Gao, Ke Chen, 2011, Structure.

On the intrinsic disorder status of the major players in programmed cell death pathways

Lukasz Kurgan, Zhenling Peng, Vladimir N Uversky, 2013, F1000Research.

Computational Prediction of MoRFs, Short Disorder-to-order Transitioning Protein Binding Regions

Lukasz Kurgan, Jianyi Yang, Zhenling Peng, 2019, Computational and structural biotechnology journal.

Prediction and characterization of cyclic proteins from sequences in three domains of life.

Lukasz Kurgan, Marcin J Mizianty, Quentin Kaas, 2014, Biochimica et biophysica acta.

How disordered is my protein and what is its disorder for? A guide through the “dark side” of the protein universe

Sonia Longhi, Lukasz Kurgan, Vladimir N. Uversky, 2016, Intrinsically disordered proteins.

Improved identification of outer membrane beta barrel proteins using primary sequence, predicted secondary structure, and evolutionary information

Lukasz Kurgan, Marcin J Mizianty, Lukasz Kurgan, 2011, Proteins.

Comprehensive review of methods for prediction of intrinsic disorder and its molecular functions

Lukasz Kurgan, Vladimir N Uversky, Fanchi Meng, 2017, Cellular and Molecular Life Sciences.

Disordered Proteinaceous Machines

Lukasz Kurgan, Monika Fuxreiter, Vladimir N. Uversky, 2014, Chemical reviews.

Unstructural biology of the dengue virus proteins

Lukasz Kurgan, Fanchi Meng, Lukasz Kurgan, 2015, The FEBS journal.

Exceptionally abundant exceptions: comprehensive characterization of intrinsic disorder in all domains of life

Lukasz Kurgan, Jing Yan, Zhenling Peng, 2014, Cellular and Molecular Life Sciences.

On the Relation Between the Predicted Secondary Structure and the Protein Size

Lukasz Kurgan, Lukasz Kurgan, 2008, The protein journal.