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iLoc-Euk: a multi-label classifier for predicting the subcellular localization of singleplex and multiplex eukaryotic proteinsNR-2L: a two-level predictor for identifying nuclear receptor subfamilies based on sequence-derived featuresA multi-label classifier for predicting the subcellular localization of gram-negative bacterial proteins with both single and multiple sitesiNR-PhysChem: a sequence-based predictor for identifying nuclear receptors and their subfamilies via physical-chemical property matrixPredicting secretory proteins of malaria parasite by incorporating sequence evolution information into pseudo amino acid composition via grey system modeliGPCR-drug: a web server for predicting interaction between GPCRs and drugs in cellular networkingiEzy-drug: a web server for identifying the interaction between enzymes and drugs in cellular networkingBenchmark data for identifying DNA methylation sites via pseudo trinucleotide composition.iMethyl-PseAAC: identification of protein methylation sites via a pseudo amino acid composition approachiDNA-Prot: identification of DNA binding proteins using random forest with grey model.iPTM-mLys: identifying multiple lysine PTM sites and their different types.Predicting protein structural classes with pseudo amino acid composition: an approach using geometric moments of cellular automaton image.GPCR-CA: A cellular automaton image approach for predicting G-protein-coupled receptor functional classes.iROS-gPseKNC: Predicting replication origin sites in DNA by incorporating dinucleotide position-specific propensity into general pseudo nucleotide composition.iCar-PseCp: identify carbonylation sites in proteins by Monte Carlo sampling and incorporating sequence coupled effects into general PseAAC.iHyd-PseCp: Identify hydroxyproline and hydroxylysine in proteins by incorporating sequence-coupled effects into general PseAAC.iPhos-PseEn: identifying phosphorylation sites in proteins by fusing different pseudo components into an ensemble classifier.iRSpot-TNCPseAAC: identify recombination spots with trinucleotide composition and pseudo amino acid componentsiNR-Drug: predicting the interaction of drugs with nuclear receptors in cellular networking.Cellular automata and its applications in protein bioinformatics.Recent progresses in identifying nuclear receptors and their families.Predict drug-protein interaction in cellular networking.Recent advances in predicting protein classification and their applications to drug development.pLoc-mEuk: Predict subcellular localization of multi-label eukaryotic proteins by extracting the key GO information into general PseAAC.pLoc-mVirus: Predict subcellular localization of multi-location virus proteins via incorporating the optimal GO information into general PseAAC.pLoc-mPlant: predict subcellular localization of multi-location plant proteins by incorporating the optimal GO information into general PseAAC.iLoc-Gpos: a multi-layer classifier for predicting the subcellular localization of singleplex and multiplex Gram-positive bacterial proteins.iLoc-Virus: a multi-label learning classifier for identifying the subcellular localization of virus proteins with both single and multiple sites.iPhos-PseEvo: Identifying Human Phosphorylated Proteins by Incorporating Evolutionary Information into General PseAAC via Grey System Theory.iATC-mISF: a multi-label classifier for predicting the classes of anatomical therapeutic chemicals.pSumo-CD: predicting sumoylation sites in proteins with covariance discriminant algorithm by incorporating sequence-coupled effects into general PseAAC.Digital coding of amino acids based on hydrophobic index.iSuc-PseOpt: Identifying lysine succinylation sites in proteins by incorporating sequence-coupling effects into pseudo components and optimizing imbalanced training dataset.Identification of protein-protein binding sites by incorporating the physicochemical properties and stationary wavelet transforms into pseudo amino acid composition.pRNAm-PC: Predicting N(6)-methyladenosine sites in RNA sequences via physical-chemical properties.iRNAm5C-PseDNC: identifying RNA 5-methylcytosine sites by incorporating physical-chemical properties into pseudo dinucleotide compositioniDrug-Target: predicting the interactions between drug compounds and target proteins in cellular networking via benchmark dataset optimization approach.iATC-mHyb: a hybrid multi-label classifier for predicting the classification of anatomical therapeutic chemicals.Erratum to "pLoc-mVirus: Predict subcellular localization of multi-location virus proteins via incorporating the optimal GO information into general PseAAC" [Gene 628 (2017) 315-321].An application of gene comparative image for predicting the effect on replication ratio by HBV virus gene missense mutation.
P50
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P50
name
Xuan Xiao
@en
Xuan Xiao
@nl
type
label
Xuan Xiao
@en
Xuan Xiao
@nl
prefLabel
Xuan Xiao
@en
Xuan Xiao
@nl