iROS-gPseKNC: Predicting replication origin sites in DNA by incorporating dinucleotide position-specific propensity into general pseudo nucleotide composition
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Kuo-Chen Chou | Xuan Xiao | Zi Liu | K. Chou | X. Xiao | J. Jia | Zi Liu | Han-Xiao Ye | Han-Xiao Ye | Jian-Hua Jia | Xuan Xiao
[1] K. Chou. Some remarks on protein attribute prediction and pseudo amino acid composition , 2010, Journal of Theoretical Biology.
[2] K. Chou,et al. pRNAm-PC: Predicting N(6)-methyladenosine sites in RNA sequences via physical-chemical properties. , 2016, Analytical biochemistry.
[3] Stephen C. J. Parker,et al. A map of minor groove shape and electrostatic potential from hydroxyl radical cleavage patterns of DNA. , 2011, ACS chemical biology.
[4] Kuo-Chen Chou,et al. Nuc-PLoc: a new web-server for predicting protein subnuclear localization by fusing PseAA composition and PsePSSM. , 2007, Protein engineering, design & selection : PEDS.
[5] K. Chou,et al. Virus-PLoc: a fusion classifier for predicting the subcellular localization of viral proteins within host and virus-infected cells. , 2007, Biopolymers.
[6] Wei Chen,et al. iORI-PseKNC: A predictor for identifying origin of replication with pseudo k-tuple nucleotide composition , 2015 .
[7] Guo-Ping Zhou. The disposition of the LZCC protein residues in wenxiang diagram provides new insights into the protein–protein interaction mechanism , 2011, Journal of Theoretical Biology.
[8] Wei Chen,et al. iTIS-PseTNC: a sequence-based predictor for identifying translation initiation site in human genes using pseudo trinucleotide composition. , 2014, Analytical biochemistry.
[9] H.-B. Shen,et al. Predicting secretory protein signal sequence cleavage sites by fusing the marks of global alignments , 2006, Amino Acids.
[10] K. Chou,et al. Prediction of protein structural classes. , 1995, Critical reviews in biochemistry and molecular biology.
[11] Dong-Sheng Cao,et al. propy: a tool to generate various modes of Chou's PseAAC , 2013, Bioinform..
[12] I. Brukner,et al. Sequence‐dependent bending propensity of DNA as revealed by DNase I: parameters for trinucleotides. , 1995, The EMBO journal.
[13] Marie-Claude Marsolier-Kergoat. Asymmetry Indices for Analysis and Prediction of Replication Origins in Eukaryotic Genomes , 2012, PloS one.
[14] Chengcheng Song,et al. Choosing a suitable method for the identification of replication origins in microbial genomes , 2015, Front. Microbiol..
[15] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[16] Tom Fawcett,et al. An introduction to ROC analysis , 2006, Pattern Recognit. Lett..
[17] J. Chou,et al. Kinetic studies with the non-nucleoside HIV-1 reverse transcriptase inhibitor U-88204E. , 1993, Biochemistry.
[18] K. Chou,et al. iRSpot-TNCPseAAC: Identify Recombination Spots with Trinucleotide Composition and Pseudo Amino Acid Components , 2014, International journal of molecular sciences.
[19] Xiaolong Wang,et al. Identification of DNA-binding proteins by incorporating evolutionary information into pseudo amino acid composition via the top-n-gram approach , 2015, Journal of biomolecular structure & dynamics.
[20] Kuo-Chen Chou,et al. iPPBS-Opt: A Sequence-Based Ensemble Classifier for Identifying Protein-Protein Binding Sites by Optimizing Imbalanced Training Datasets , 2016, Molecules.
[21] K. Chou. Structural bioinformatics and its impact to biomedical science. , 2004, Current medicinal chemistry.
[22] K. Chou,et al. iGPCR-Drug: A Web Server for Predicting Interaction between GPCRs and Drugs in Cellular Networking , 2013, PloS one.
[23] Kuo-Chen Chou,et al. Signal-CF: a subsite-coupled and window-fusing approach for predicting signal peptides. , 2007, Biochemical and biophysical research communications.
[24] Sung Moon Kim,et al. DNA cleavage by hydroxyl radicals generated in the Cu,Zn-superoxide dismutase and hydrogen peroxide system. , 1997, Molecules and cells.
[25] Mark Goadrich,et al. The relationship between Precision-Recall and ROC curves , 2006, ICML.
[26] Kuo-Chen Chou,et al. Identification of protein-protein binding sites by incorporating the physicochemical properties and stationary wavelet transforms into pseudo amino acid composition , 2016, Journal of biomolecular structure & dynamics.
[27] K. Chou,et al. iMethyl-PseAAC: Identification of Protein Methylation Sites via a Pseudo Amino Acid Composition Approach , 2014, BioMed research international.
[28] Kuo-Chen Chou,et al. Prediction of Membrane Protein Types by Incorporating Amphipathic Effects , 2005, J. Chem. Inf. Model..
[29] Junjie Chen,et al. Pse-in-One: a web server for generating various modes of pseudo components of DNA, RNA, and protein sequences , 2015, Nucleic Acids Res..
[30] K. Chou,et al. iRNA-Methyl: Identifying N(6)-methyladenosine sites using pseudo nucleotide composition. , 2015, Analytical biochemistry.
[31] K. Chou,et al. iNitro-Tyr: Prediction of Nitrotyrosine Sites in Proteins with General Pseudo Amino Acid Composition , 2014, PloS one.
[32] Xiaolong Wang,et al. repRNA: a web server for generating various feature vectors of RNA sequences , 2015, Molecular Genetics and Genomics.
[33] K. Chou,et al. iACP: a sequence-based tool for identifying anticancer peptides , 2016, Oncotarget.
[34] Maqsood Hayat,et al. iRSpot-GAEnsC: identifing recombination spots via ensemble classifier and extending the concept of Chou’s PseAAC to formulate DNA samples , 2015, Molecular Genetics and Genomics.
[35] K. Chou. Graphic rule for drug metabolism systems. , 2010, Current drug metabolism.
[36] K D Watenpaugh,et al. A model of the complex between cyclin-dependent kinase 5 and the activation domain of neuronal Cdk5 activator. , 1999, Biochemical and biophysical research communications.
[37] K. Chou,et al. ProtIdent: a web server for identifying proteases and their types by fusing functional domain and sequential evolution information. , 2008, Biochemical and biophysical research communications.
[38] Maqsood Hayat,et al. Author ' s Accepted Manuscript Classification of membrane protein types using Voting feature interval in combination with Chou ' s pseudo amino acid composition , 2015 .
[39] Kuo-Chen Chou,et al. pSuc-Lys: Predict lysine succinylation sites in proteins with PseAAC and ensemble random forest approach. , 2016, Journal of theoretical biology.
[40] K. Chou. Prediction of protein cellular attributes using pseudo‐amino acid composition , 2001, Proteins.
[41] K. Chou,et al. iEzy-Drug: A Web Server for Identifying the Interaction between Enzymes and Drugs in Cellular Networking , 2013, BioMed research international.
[42] K. Chou. Prediction of signal peptides using scaled window , 2001, Peptides.
[43] K. Chou,et al. iLoc-Hum: using the accumulation-label scale to predict subcellular locations of human proteins with both single and multiple sites. , 2012, Molecular bioSystems.
[44] Kuo-Chen Chou,et al. Using amphiphilic pseudo amino acid composition to predict enzyme subfamily classes , 2005, Bioinform..
[45] K. Chou,et al. Pseudo nucleotide composition or PseKNC: an effective formulation for analyzing genomic sequences. , 2015, Molecular bioSystems.
[46] Wei Chen,et al. iNuc-PseKNC: a sequence-based predictor for predicting nucleosome positioning in genomes with pseudo k-tuple nucleotide composition , 2014, Bioinform..
[47] Jiangning Song,et al. Prediction of protein folding rates from primary sequence by fusing multiple sequential features , 2009 .
[48] K. Chou,et al. iHSP-PseRAAAC: Identifying the heat shock protein families using pseudo reduced amino acid alphabet composition. , 2013, Analytical biochemistry.
[49] Wei Chen,et al. PseKNC-General: a cross-platform package for generating various modes of pseudo nucleotide compositions , 2015, Bioinform..
[50] K. Chou. Applications of graph theory to enzyme kinetics and protein folding kinetics. Steady and non-steady-state systems. , 2020, Biophysical chemistry.
[51] Kuo-Chen Chou,et al. Predicting eukaryotic protein subcellular location by fusing optimized evidence-theoretic K-Nearest Neighbor classifiers. , 2006, Journal of proteome research.
[52] K. Chou,et al. Wenxiang: a web-server for drawing wenxiang diagrams , 2011 .
[53] K. Chou,et al. Recent progress in protein subcellular location prediction. , 2007, Analytical biochemistry.
[54] Kuo-Chen Chou,et al. Predicting protein subcellular location by fusing multiple classifiers , 2006, Journal of cellular biochemistry.
[55] K. Chou,et al. iSNO-PseAAC: Predict Cysteine S-Nitrosylation Sites in Proteins by Incorporating Position Specific Amino Acid Propensity into Pseudo Amino Acid Composition , 2013, PloS one.
[56] Kuo-Chen Chou,et al. iPPI-Esml: An ensemble classifier for identifying the interactions of proteins by incorporating their physicochemical properties and wavelet transforms into PseAAC. , 2015, Journal of theoretical biology.
[57] K. Chou,et al. Prediction of linear B-cell epitopes using amino acid pair antigenicity scale , 2007, Amino Acids.
[58] Xiang Cheng,et al. iDrug-Target: predicting the interactions between drug compounds and target proteins in cellular networking via benchmark dataset optimization approach , 2015, Journal of biomolecular structure & dynamics.
[59] K. Chou,et al. iUbiq-Lys: prediction of lysine ubiquitination sites in proteins by extracting sequence evolution information via a gray system model , 2015, Journal of biomolecular structure & dynamics.
[60] Sourav Chatterji,et al. Prediction of Saccharomyces cerevisiae replication origins , 2004, Genome Biology.
[61] K. Chou. Pseudo Amino Acid Composition and its Applications in Bioinformatics, Proteomics and System Biology , 2009 .
[62] Kuo-Chen Chou,et al. RSARF: prediction of residue solvent accessibility from protein sequence using random forest method. , 2012, Protein and peptide letters.
[63] L. Resnick,et al. The quinoline U-78036 is a potent inhibitor of HIV-1 reverse transcriptase. , 1993, The Journal of biological chemistry.
[64] Pufeng Du,et al. PseAAC-General: Fast Building Various Modes of General Form of Chou’s Pseudo-Amino Acid Composition for Large-Scale Protein Datasets , 2014, International journal of molecular sciences.
[65] K. Chou,et al. iSNO-AAPair: incorporating amino acid pairwise coupling into PseAAC for predicting cysteine S-nitrosylation sites in proteins , 2013, PeerJ.
[66] Kuo-Chen Chou,et al. Sequence analysis iEnhancer-2 L : a two-layer predictor for identifying enhancers and their strength by pseudo k-tuple nucleotide composition , 2016 .
[67] Dagmara Jakimowicz,et al. Regulation of the initiation of chromosomal replication in bacteria. , 2007, FEMS microbiology reviews.
[68] S. Forsén,et al. Graphical rules for enzyme-catalysed rate laws. , 1980, The Biochemical journal.
[69] K. Chou,et al. 2D-MH: A web-server for generating graphic representation of protein sequences based on the physicochemical properties of their constituent amino acids. , 2010, Journal of theoretical biology.
[70] Kuo-Chen Chou,et al. iSuc-PseOpt: Identifying lysine succinylation sites in proteins by incorporating sequence-coupling effects into pseudo components and optimizing imbalanced training dataset. , 2016, Analytical biochemistry.
[71] K. Chou,et al. iDNA-Prot: Identification of DNA Binding Proteins Using Random Forest with Grey Model , 2011, PloS one.
[72] K. Chou,et al. iAMP-2L: a two-level multi-label classifier for identifying antimicrobial peptides and their functional types. , 2013, Analytical biochemistry.
[73] K. Chou,et al. iLoc-Plant: a multi-label classifier for predicting the subcellular localization of plant proteins with both single and multiple sites. , 2011, Molecular bioSystems.
[74] Kuo-Chen Chou,et al. Some remarks on predicting multi-label attributes in molecular biosystems. , 2013, Molecular bioSystems.
[75] Chou Kuo-Chen,et al. GRAPH THEORY OF ENZYME KINETICS I.STEADY-STATE REACTION SYSTEMS , 1979 .
[76] Kuo-Chen Chou,et al. iNR-Drug: Predicting the Interaction of Drugs with Nuclear Receptors in Cellular Networking , 2014, International journal of molecular sciences.
[77] Wei Chen,et al. Prediction of replication origins by calculating DNA structural properties , 2012, FEBS letters.
[78] Xiaolong Wang,et al. Combining evolutionary information extracted from frequency profiles with sequence-based kernels for protein remote homology detection , 2013, Bioinform..
[79] Wei Chen,et al. iRSpot-PseDNC: identify recombination spots with pseudo dinucleotide composition , 2013, Nucleic acids research.
[80] K. Chou,et al. iSS-PseDNC: Identifying Splicing Sites Using Pseudo Dinucleotide Composition , 2014, BioMed research international.
[81] K. Chou,et al. PseKNC: a flexible web server for generating pseudo K-tuple nucleotide composition. , 2014, Analytical biochemistry.
[82] K. Chou,et al. iLoc-Animal: a multi-label learning classifier for predicting subcellular localization of animal proteins. , 2013, Molecular bioSystems.
[83] K. Chou. Impacts of bioinformatics to medicinal chemistry. , 2015, Medicinal chemistry (Shariqah (United Arab Emirates)).
[84] P. Suganthan,et al. AFP-Pred: A random forest approach for predicting antifreeze proteins from sequence-derived properties. , 2011, Journal of theoretical biology.
[85] K. Chou,et al. iHyd-PseAAC: Predicting Hydroxyproline and Hydroxylysine in Proteins by Incorporating Dipeptide Position-Specific Propensity into Pseudo Amino Acid Composition , 2014, International journal of molecular sciences.
[86] K. Chou,et al. iCTX-Type: A Sequence-Based Predictor for Identifying the Types of Conotoxins in Targeting Ion Channels , 2014, BioMed research international.
[87] Kuo-Chen Chou,et al. QuatIdent: a web server for identifying protein quaternary structural attribute by fusing functional domain and sequential evolution information. , 2009, Journal of proteome research.
[88] Wei Chen,et al. iPro54-PseKNC: a sequence-based predictor for identifying sigma-54 promoters in prokaryote with pseudo k-tuple nucleotide composition , 2014, Nucleic acids research.
[89] K. Chou,et al. Virus-mPLoc: A Fusion Classifier for Viral Protein Subcellular Location Prediction by Incorporating Multiple Sites , 2010, Journal of biomolecular structure & dynamics.
[90] Xiaolong Wang,et al. repDNA: a Python package to generate various modes of feature vectors for DNA sequences by incorporating user-defined physicochemical properties and sequence-order effects , 2015, Bioinform..
[91] K. Chou,et al. Euk-mPLoc: a fusion classifier for large-scale eukaryotic protein subcellular location prediction by incorporating multiple sites. , 2007, Journal of proteome research.
[92] K. Chou,et al. iCDI-PseFpt: identify the channel-drug interaction in cellular networking with PseAAC and molecular fingerprints. , 2013, Journal of theoretical biology.
[93] Kuo-Chen Chou,et al. Prediction of the tertiary structure of the beta-secretase zymogen. , 2002, Biochemical and biophysical research communications.
[94] G. Zhou,et al. An extension of Chou's graphic rules for deriving enzyme kinetic equations to systems involving parallel reaction pathways. , 1984, The Biochemical journal.
[95] Manish Kumar,et al. Prediction of β-lactamase and its class by Chou's pseudo-amino acid composition and support vector machine. , 2015, Journal of theoretical biology.
[96] Zaheer Ullah Khan,et al. Discrimination of acidic and alkaline enzyme using Chou's pseudo amino acid composition in conjunction with probabilistic neural network model. , 2015, Journal of theoretical biology.