Lukasz Kurgan

Summary

Affiliation: University of Alberta
Country: Canada

Publications

  1. doi The intrinsic disorder status of the human hepatitis C virus proteome
    Xiao Fan
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta AB T6G 2V4, Canada
    Mol Biosyst 10:1345-63. 2014
  2. ncbi CRYSpred: accurate sequence-based protein crystallization propensity prediction using sequence-derived structural characteristics
    Marcin J Mizianty
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, Canada
    Protein Pept Lett 19:40-9. 2012
  3. pmc Prediction of flexible/rigid regions from protein sequences using k-spaced amino acid pairs
    Ke Chen
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada
    BMC Struct Biol 7:25. 2007
  4. pmc Sequence based residue depth prediction using evolutionary information and predicted secondary structure
    Hua Zhang
    College of Mathematical Science and LPMC, Nankai University, Tianjin, PR China
    BMC Bioinformatics 9:388. 2008
  5. pmc Improved machine learning method for analysis of gas phase chemistry of peptides
    Allison Gehrke
    Department of Computer Science and Engineering, University of Colorado at Denver, USA
    BMC Bioinformatics 9:515. 2008
  6. doi Secondary structure-based assignment of the protein structural classes
    Lukasz A Kurgan
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada
    Amino Acids 35:551-64. 2008
  7. doi Critical assessment of high-throughput standalone methods for secondary structure prediction
    Hua Zhang
    Zhejiang Gongshang University, Hangzhou, Zhejiang, P R China
    Brief Bioinform 12:672-88. 2011
  8. pmc ATPsite: sequence-based prediction of ATP-binding residues
    Ke Chen
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada
    Proteome Sci 9:S4. 2011
  9. pmc CRYSTALP2: sequence-based protein crystallization propensity prediction
    Lukasz Kurgan
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, Canada
    BMC Struct Biol 9:50. 2009
  10. pmc SCPRED: accurate prediction of protein structural class for sequences of twilight-zone similarity with predicting sequences
    Lukasz Kurgan
    Department of Electrical and Computer Engineering, University of Alberta, ECEFR, 9701 116 Street, Edmonton, AB, T6G 2V4, Canada
    BMC Bioinformatics 9:226. 2008

Collaborators

Detail Information

Publications71

  1. doi The intrinsic disorder status of the human hepatitis C virus proteome
    Xiao Fan
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta AB T6G 2V4, Canada
    Mol Biosyst 10:1345-63. 2014
    ....
  2. ncbi CRYSpred: accurate sequence-based protein crystallization propensity prediction using sequence-derived structural characteristics
    Marcin J Mizianty
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, Canada
    Protein Pept Lett 19:40-9. 2012
    ..The inputs utilized by CRYSpred are well-aligned with the existing rules-of-thumb that are used in the structural genomics studies...
  3. pmc Prediction of flexible/rigid regions from protein sequences using k-spaced amino acid pairs
    Ke Chen
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada
    BMC Struct Biol 7:25. 2007
    ..Knowledge of the flexible/rigid regions may provide insights into the protein folding process and the 3D structure prediction...
  4. pmc Sequence based residue depth prediction using evolutionary information and predicted secondary structure
    Hua Zhang
    College of Mathematical Science and LPMC, Nankai University, Tianjin, PR China
    BMC Bioinformatics 9:388. 2008
    ..Accurate prediction of residue depth would provide valuable information for fold recognition, prediction of functional sites, and protein design...
  5. pmc Improved machine learning method for analysis of gas phase chemistry of peptides
    Allison Gehrke
    Department of Computer Science and Engineering, University of Colorado at Denver, USA
    BMC Bioinformatics 9:515. 2008
    ..Improved discrimination is achieved with theoretical spectra that are based on simulating gas phase chemistry of the peptides, but the limited understanding of those processes affects the accuracy of predictions from theoretical spectra...
  6. doi Secondary structure-based assignment of the protein structural classes
    Lukasz A Kurgan
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada
    Amino Acids 35:551-64. 2008
    ..Therefore, PSSA(sc) can be used to perform the automated assignment of structural classes based on the sequences...
  7. doi Critical assessment of high-throughput standalone methods for secondary structure prediction
    Hua Zhang
    Zhejiang Gongshang University, Hangzhou, Zhejiang, P R China
    Brief Bioinform 12:672-88. 2011
    ..Finally, we compare predictions of the standalone implementations of four well-performing methods with their corresponding web servers...
  8. pmc ATPsite: sequence-based prediction of ATP-binding residues
    Ke Chen
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada
    Proteome Sci 9:S4. 2011
    ..Moreover, our empirical tests show that the only existing predictor, ATPint, is characterized by relatively low predictive quality...
  9. pmc CRYSTALP2: sequence-based protein crystallization propensity prediction
    Lukasz Kurgan
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, Canada
    BMC Struct Biol 9:50. 2009
    ..CRYSTALP2 extends its predecessor, CRYSTALP, by enabling predictions for sequences of unrestricted size and provides improved prediction quality...
  10. pmc SCPRED: accurate prediction of protein structural class for sequences of twilight-zone similarity with predicting sequences
    Lukasz Kurgan
    Department of Electrical and Computer Engineering, University of Alberta, ECEFR, 9701 116 Street, Edmonton, AB, T6G 2V4, Canada
    BMC Bioinformatics 9:226. 2008
    ..We propose SCPRED method that improves prediction accuracy for sequences that share twilight-zone pairwise similarity with sequences used for the prediction...
  11. doi On the relation between the predicted secondary structure and the protein size
    Lukasz Kurgan
    Department of Electrical and Computer Engineering, University of Alberta, 2nd Floor, ECERF 9107 116 Street, Edmonton, AB, Canada T6G 2V4
    Protein J 27:234-9. 2008
    ..This is in contrast with the tertiary structure predictions in which higher accuracy is obtained for smaller proteins...
  12. ncbi Novel scales based on hydrophobicity indices for secondary protein structure
    Lukasz A Kurgan
    Electrical and Computer Engineering Department, University of Alberta, Edmonton, Canada, T6G 2V4
    J Theor Biol 248:354-66. 2007
    ..In contrast, the Fauchere-Pliska's index is found to perform better when compared with the two other indices when using raw hydrophobic index values that disregard the long-range interactions...
  13. ncbi Structural protein descriptors in 1-dimension and their sequence-based predictions
    Lukasz Kurgan
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada
    Curr Protein Pept Sci 12:470-89. 2011
    ..We demonstrate that the secondary structure predicted from sequence without the use of homology modeling is as good as the structure extracted from the 3D folds predicted by top-performing template-based methods...
  14. ncbi Prediction of protein structural class for the twilight zone sequences
    Lukasz Kurgan
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, Canada
    Biochem Biophys Res Commun 357:453-60. 2007
    ....
  15. ncbi Sequence representation and prediction of protein secondary structure for structural motifs in twilight zone proteins
    Lukasz Kurgan
    Electrical and Computer Engineering Department, University of Alberta, Edmonton, Alberta, Canada, T6G 2V4
    Protein J 25:463-74. 2006
    ..Finally, we show that certain prediction algorithms, such as neural networks and boosted decision trees, are superior to other algorithms...
  16. pmc Improved sequence-based prediction of disordered regions with multilayer fusion of multiple information sources
    Marcin J Mizianty
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada
    Bioinformatics 26:i489-96. 2010
    ..Although the prediction quality of these methods continues to rise, novel and improved predictors are urgently needed...
  17. doi Genome-scale prediction of proteins with long intrinsically disordered regions
    Zhenling Peng
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada
    Proteins 82:145-58. 2014
    ..A webserver that implements SLIDER is available at http://biomine.ece.ualberta.ca/SLIDER/...
  18. pmc MoRFpred, a computational tool for sequence-based prediction and characterization of short disorder-to-order transitioning binding regions in proteins
    Fatemeh Miri Disfani
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, T6G 2V4, Canada
    Bioinformatics 28:i75-83. 2012
    ..However, only a limited number of experimentally validated MoRFs is known, which motivates development of computational methods that predict MoRFs from protein chains...
  19. doi A creature with a hundred waggly tails: intrinsically disordered proteins in the ribosome
    Zhenling Peng
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, T6G 2V4, Canada
    Cell Mol Life Sci 71:1477-504. 2014
    ..Furthermore, intrinsic disorder is not only abundant in the ribosomal proteins, but we demonstrate that it is absolutely necessary for their various functions. ..
  20. ncbi PFRES: protein fold classification by using evolutionary information and predicted secondary structure
    Ke Chen
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada
    Bioinformatics 23:2843-50. 2007
    ..At the same time, some proteins that share twilight-zone sequence identity can form similar folds. Therefore, determination of structural similarity without sequence similarity would be beneficial for prediction of tertiary structures...
  21. pmc Prediction of beta-turns at over 80% accuracy based on an ensemble of predicted secondary structures and multiple alignments
    Ce Zheng
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada
    BMC Bioinformatics 9:430. 2008
    ....
  22. doi Prediction of integral membrane protein type by collocated hydrophobic amino acid pairs
    Ke Chen
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, Canada
    J Comput Chem 30:163-72. 2009
    ..This conclusion is supported by a recent study on potential of mean force for membrane protein folding and a study of scales for membrane propensity of amino acids...
  23. ncbi Improved sequence-based prediction of strand residues
    Kanaka Durga Kedarisetti
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada
    J Bioinform Comput Biol 9:67-89. 2011
    ..When compared with the ZHANG-server, we improve predictions of strand segments and predict more actual strand residues, while the other predictor achieves higher rate of correct strand residue predictions when under-predicting them...
  24. doi Exceptionally abundant exceptions: comprehensive characterization of intrinsic disorder in all domains of life
    Zhenling Peng
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada
    Cell Mol Life Sci 72:137-51. 2015
    ..We provide a complete analysis that clearly shows that intrinsic disorder is exceptionally and uniquely abundant in each domain of life. ..
  25. doi Computational prediction of secondary and supersecondary structures
    Ke Chen
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada
    Methods Mol Biol 932:63-86. 2013
    ..Finally, we provide several practical notes for the users of these prediction tools...
  26. pmc Modular prediction of protein structural classes from sequences of twilight-zone identity with predicting sequences
    Marcin J Mizianty
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada
    BMC Bioinformatics 10:414. 2009
    ....
  27. doi A critical comparative assessment of predictions of protein-binding sites for biologically relevant organic compounds
    Ke Chen
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB T6G 2V4, Canada
    Structure 19:613-21. 2011
    ..Predictions from these four methods are complementary, and our simple meta-predictor improves over the best single predictor...
  28. doi Identification of tubulin drug binding sites and prediction of relative differences in binding affinities to tubulin isotypes using digital signal processing
    Ke Chen
    Department of Electrical and Computer Engineering, University of Alberta, ECEFR, 9701 116 Street, Edmonton, AB, Canada T6G2V4
    J Mol Graph Model 27:497-505. 2008
    ..Additionally, the DSP method enables the rapid estimation of relative differences in binding affinities within the binding sites of tubulin isotypes that are yet to be experimentally determined...
  29. ncbi Prediction of protein crystallization using collocation of amino acid pairs
    Ke Chen
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alta, Canada
    Biochem Biophys Res Commun 355:764-9. 2007
    ..CRYSTALP uses different and over 50% less features to represent sequences than SECRET. Additionally, features used by CRYSTALP may help to discover intra-molecular markers that influence protein crystallization...
  30. doi PDID: database of molecular-level putative protein-drug interactions in the structural human proteome
    Chen Wang
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada T6G 2V4
    Bioinformatics 32:579-86. 2016
    ..Protein-Drug Interaction Database (PDID) addresses incompleteness of these data by providing access to putative protein-drug interactions that cover the entire structural human proteome...
  31. doi Molecular recognition features (MoRFs) in three domains of life
    Jing Yan
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, T6G 2V4, Canada
    Mol Biosyst 12:697-710. 2016
    ..The fMoRFpred method that we used to annotate MoRFs is available at http://biomine.ece.ualberta.ca/fMoRFpred/...
  32. pmc In-silico prediction of disorder content using hybrid sequence representation
    Marcin J Mizianty
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta T6G 2V4, Canada
    BMC Bioinformatics 12:245. 2011
    ..We show that these predictions may over-or under-predict the overall amount of disorder, which motivates development of novel tools for direct and accurate sequence-based prediction of the disorder content...
  33. pmc Sequence-based Gaussian network model for protein dynamics
    Hua Zhang
    School of Computer and Information Engineering, Zhejiang Gongshang University, Hangzhou, Zhejiang 310018, P R China and Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta T6G 2V4, Canada
    Bioinformatics 30:497-505. 2014
    ..The existing GNM-based approaches require atomic coordinates of the corresponding protein and cannot be used when only the sequence is known...
  34. doi RAPID: fast and accurate sequence-based prediction of intrinsic disorder content on proteomic scale
    Jing Yan
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada
    Biochim Biophys Acta 1834:1671-80. 2013
    ..RAPID, which allows for batch (proteome-wide) predictions, is available as a web server at http://biomine.ece.ualberta.ca/RAPID/. ..
  35. ncbi Comprehensive comparative assessment of in-silico predictors of disordered regions
    Zhen Ling Peng
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada
    Curr Protein Pept Sci 13:6-18. 2012
    ..Lastly, we provide recommendations concerning development of a new generation of consensusbased methods and specialized methods for improved prediction of the disorder content...
  36. ncbi A comment on "Prediction of protein structural classes by a new measure of information discrepancy"
    Kanaka Durga Kedarisetti
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alta, Canada
    Comput Biol Chem 30:393-4. 2006
    ..Comput. Biol. Chem. 27, 373-380], which gave high prediction accuracy on a low homology dataset, and we empirically confirmed that the reported results were an artifact of improper implementation...
  37. doi iFC²: an integrated web-server for improved prediction of protein structural class, fold type, and secondary structure content
    Ke Chen
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, Canada
    Amino Acids 40:963-73. 2011
    ..The iFC² server is available at http://biomine.ece.ualberta.ca/1D/1D.html ...
  38. ncbi Classifier ensembles for protein structural class prediction with varying homology
    Kanaka Durga Kedarisetti
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alta, Canada
    Biochem Biophys Res Commun 348:981-8. 2006
    ..Comparisons with competing methods on three large benchmark datasets consistently show the superiority of the proposed method...
  39. pmc Compartmentalization and Functionality of Nuclear Disorder: Intrinsic Disorder and Protein-Protein Interactions in Intra-Nuclear Compartments
    Fanchi Meng
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB T6G 2V4, Canada
    Int J Mol Sci 17:. 2015
    ....
  40. doi Meta prediction of protein crystallization propensity
    Marcin J Mizianty
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alta, Canada
    Biochem Biophys Res Commun 390:10-5. 2009
    ..8. The proposed method could provide useful input for target selection procedures of current structural genomics efforts...
  41. pmc Sequence-based prediction of protein crystallization, purification and production propensity
    Marcin J Mizianty
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada
    Bioinformatics 27:i24-33. 2011
    ....
  42. pmc Investigation of atomic level patterns in protein--small ligand interactions
    Ke Chen
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, Canada
    PLoS ONE 4:e4473. 2009
    ..We investigate the role of covalent and non-covalent bonds in protein-small ligand interactions using a comprehensive dataset of 2,320 complexes...
  43. doi Comprehensively designed consensus of standalone secondary structure predictors improves Q3 by over 3%
    Jing Yan
    a Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada
    J Biomol Struct Dyn 32:36-51. 2014
    ..Case studies are used to visualize the improvements offered by the consensus at the residue level. A web-server and a standalone implementation of SScon are available at http://biomine.ece.ualberta.ca/SSCon/ ...
  44. doi Prediction and characterization of cyclic proteins from sequences in three domains of life
    Pradyumna Kedarisetti
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, T6G 2V4, Canada
    Biochim Biophys Acta 1844:181-90. 2014
    ..ece.ualberta.ca/CyPred/. This article is part of a Special Issue entitled: Computational Proteomics, Systems Biology & Clinical Implications. Guest Editor: Yudong Cai. ..
  45. doi More than just tails: intrinsic disorder in histone proteins
    Zhenling Peng
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada
    Mol Biosyst 8:1886-901. 2012
    ....
  46. doi Improved identification of outer membrane beta barrel proteins using primary sequence, predicted secondary structure, and evolutionary information
    Marcin J Mizianty
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, Canada
    Proteins 79:294-303. 2011
    ..Our solution is a useful tool for high-throughput discovery of the OMBBs on a genome scale and can be found at http://biomine.ece. ualberta.ca/OMBBpred/OMBBpred.htm...
  47. ncbi Multilabel associative classification categorization of MEDLINE articles into MeSH keywords
    Rafal Rak
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada
    IEEE Eng Med Biol Mag 26:47-55. 2007
    ..A tradeoff can be obtained by using a configuration that optimizes the average between macro and micro F1...
  48. pmc Human structural proteome-wide characterization of Cyclosporine A targets
    Gang Hu
    School of Mathematical Sciences and LPMC, Nankai University, Tianjin, 300071, PR China, Department of Biochemistry, Faculty of Pharmacy and Pharmaceutical Sciences, Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, T6G 2R3, Canada and State Key Laboratory for Medicinal Chemical Biology, Nankai University, Tianjin, 300071, PR China
    Bioinformatics 30:3561-6. 2014
    ....
  49. pmc Covering complete proteomes with X-ray structures: a current snapshot
    Marcin J Mizianty
    Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta T6G 2V4, Canada
    Acta Crystallogr D Biol Crystallogr 70:2781-93. 2014
    ..It is demonstrated that the human proteome has one of the highest attainable coverage values among eukaryotes, and GPCR membrane proteins suitable for X-ray structure determination were determined. ..
  50. doi Prediction of protein folding rates from primary sequences using hybrid sequence representation
    Yingfu Jiang
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, Canada, T6G 2V4
    J Comput Chem 30:772-83. 2009
    ..Finally, PPFR provides strong correlation when predicting sequences with low similarity...
  51. pmc HuMiTar: a sequence-based method for prediction of human microRNA targets
    Jishou Ruan
    Department of Electrical and Computer Engineering, University of Alberta, Canada
    Algorithms Mol Biol 3:16. 2008
    ..However, in the case of the traditional methods research shows that some seed region matches that are conserved are false positives and that some of the experimentally validated target sites are not conserved...
  52. doi Accurate prediction of disorder in protein chains with a comprehensive and empirically designed consensus
    Xiao Fan
    a Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, Canada
    J Biomol Struct Dyn 32:448-64. 2014
    ..disCoP is available at http://biomine.ece.ualberta.ca/disCoP/...
  53. pmc Interplay between the oxidoreductase PDIA6 and microRNA-322 controls the response to disrupted endoplasmic reticulum calcium homeostasis
    Jody Groenendyk
    Department of Biochemistry, University of Alberta, Edmonton, Alberta T6G 2S7, Canada
    Sci Signal 7:ra54. 2014
    ..Together, these findings demonstrated that ER Ca2+, PDIA6, IRE1α, and miR-322 function in a dynamic feedback loop modulating the UPR under conditions of disrupted ER Ca2+ homeostasis...
  54. pmc Intrinsic disorder in the BK channel and its interactome
    Zhenling Peng
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, Canada
    PLoS ONE 9:e94331. 2014
    ..The disordered structure of BK and its BKAPs suggests one of the underlying mechanisms of their interaction...
  55. doi Prediction and analysis of nucleotide-binding residues using sequence and sequence-derived structural descriptors
    Ke Chen
    School of Computer Science and Software Engineering, Tianjin Polytechnic University, Hedong District, Tianjin 300160, PR of China
    Bioinformatics 28:331-41. 2012
    ..The knowledge of the nucleotide-protein interactions helps with annotation of protein functions and finds applications in drug design...
  56. doi Prediction of protein structural class using novel evolutionary collocation-based sequence representation
    Ke Chen
    Department of Electrical and Computer Engineering, ECERF, University of Alberta, Edmonton, Alberta, Canada
    J Comput Chem 29:1596-604. 2008
    ..A web server that implements the presented prediction method is freely available at http://biomine.ece.ualberta.ca/Structural_Class/SCEC.html...
  57. pmc DRNApred, fast sequence-based method that accurately predicts and discriminates DNA- and RNA-binding residues
    Jing Yan
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton T6G 2V4, Canada
    Nucleic Acids Res . 2017
    ..Webserver of DRNApred is freely available at http://biomine.cs.vcu.edu/servers/DRNApred/...
  58. ncbi On the complementarity of the consensus-based disorder prediction
    Zhenling Peng
    Electrical and Computer Engineering Department, University of Alberta, Edmonton, AB, Canada
    Pac Symp Biocomput . 2012
    ..Our study provides insights that could lead to the development of a new generation of the consensus-based disorder predictors...
  59. pmc DFLpred: High-throughput prediction of disordered flexible linker regions in protein sequences
    Fanchi Meng
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton T6G 2V4, Canada
    Bioinformatics 32:i341-i350. 2016
    ..To date, there are no computational methods that directly predict DFLs and they can be found only indirectly by filtering predicted flexible residues with predictions of disorder...
  60. doi Computational Prediction of Protein Secondary Structure from Sequence
    Fanchi Meng
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada
    Curr Protoc Protein Sci 86:2.3.1-2.3.10. 2016
    ..We emphasize that modern predictors are available to end users in the form of convenient-to-use Web servers and stand-alone software. © 2016 by John Wiley & Sons, Inc...
  61. doi Unstructural biology of the Dengue virus proteins
    Fanchi Meng
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, Canada
    FEBS J 282:3368-94. 2015
    ..These regions are also associated with phosphorylation, which may regulate their function...
  62. pmc High-throughput prediction of RNA, DNA and protein binding regions mediated by intrinsic disorder
    Zhenling Peng
    Center for Applied Mathematics, Tianjin University, Tianjin, 300072, P R China Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, T6G 2V4, Canada
    Nucleic Acids Res 43:e121. 2015
    ..Webserver: http://biomine.ece.ualberta.ca/DisoRDPbind/. ..
  63. doi Prediction of intrinsic disorder in proteins using MFDp2
    Marcin J Mizianty
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada
    Methods Mol Biol 1137:147-62. 2014
    ..MFDp2 is freely available at http://biomine.ece.ualberta.ca/MFDp2/...
  64. pmc The roles of beta-tubulin mutations and isotype expression in acquired drug resistance
    J Torin Huzil
    Department of Oncology, University of Alberta, Edmonton, Alberta, Canada
    Cancer Inform 3:159-81. 2007
    ....
  65. ncbi Highly scalable and robust rule learner: performance evaluation and comparison
    Lukasz A Kurgan
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton AB T6G 2VF, Canada
    IEEE Trans Syst Man Cybern B Cybern 36:32-53. 2006
    ..DataSqueezer is thus well suited to modern data mining and business intelligence tasks, which commonly involve huge datasets with a large fraction of missing data...
  66. ncbi Prediction of protein secondary structure content for the twilight zone sequences
    Leila Homaeian
    Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, Canada
    Proteins 69:486-98. 2007
    ..At the same time, it also provides useful insight into design of successful protein sequence representations that can be used in developing new methods related to prediction of different aspects of the secondary protein structure...
  67. ncbi Machine learning in the life sciences
    Krzysztof J Cios
    University of Colorado at Denver and Health Sciences Center, USA
    IEEE Eng Med Biol Mag 26:14-6. 2007
  68. ncbi Quantitative analysis of the conservation of the tertiary structure of protein segments
    Jishou Ruan
    Chern Institute of Mathematics, College of Mathematical Science and LPMC, Nankai University, Tianjin 300071, P R China
    Protein J 25:301-15. 2006
    ..At the same time, the remaining 2% of the sequences may pose problems for the sequence alignment based structure prediction methods...
  69. ncbi Prediction of three dimensional structure of calmodulin
    Ke Chen
    College of Mathematical Sciences and LPMC, Chern Institute of Mathematics and Liuhui Center for Applied Mathematics, Nankai University, Tianjin, 300071, Peoples Republic of China
    Protein J 25:57-70. 2006
    ..The prediction results provide useful and accurate information about the structure verifying high quality of the proposed prediction method and performed structural analysis...
  70. ncbi Highly accurate and consistent method for prediction of helix and strand content from primary protein sequences
    Jishou Ruan
    College of Mathematics and LPMC, Nankai University, Tianjin 300071, PR China
    Artif Intell Med 35:19-35. 2005
    ..e. the same composition vectors correspond to different contents. To this end, we propose a method for prediction of helix/strand content from primary protein sequences that is fundamentally different from currently available methods...