iCar-PseCp: identify carbonylation sites in proteins by Monte Carlo sampling and incorporating sequence coupled effects into general PseAAC.
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Predicting antimicrobial peptides with improved accuracy by incorporating the compositional, physico-chemical and structural features into Chou's general PseAAC.2L-piRNA: A Two-Layer Ensemble Classifier for Identifying Piwi-Interacting RNAs and Their Function.Molecular classification of prostate adenocarcinoma by the integrated somatic mutation profiles and molecular networkPrediction of presynaptic and postsynaptic neurotoxins by combining various Chou's pseudo components.Pse-Analysis: a python package for DNA/RNA and protein/ peptide sequence analysis based on pseudo components and kernel methods.ProFold: Protein Fold Classification with Additional Structural Features and a Novel Ensemble ClassifierPredicting Protein-Protein Interaction Sites Using Sequence Descriptors and Site Propensity of Neighboring Amino Acids.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.Construction and analysis of dysregulated lncRNA-associated ceRNA network identified novel lncRNA biomarkers for early diagnosis of human pancreatic cancer.Genome-Wide Prediction of DNA Methylation Using DNA Composition and Sequence Complexity in HumanpLoc-mPlant: predict subcellular localization of multi-location plant proteins by incorporating the optimal GO information into general PseAAC.Estimating the effects of transcription factors binding and histone modifications on gene expression levels in human cells.Potential drug-drug interactions in paediatric outpatient prescriptions in Nigeria and implications for the future.Identification of potential CCR5 inhibitors through pharmacophore-based virtual screening, molecular dynamics simulation and binding free energy analysis.iOri-Human: identify human origin of replication by incorporating dinucleotide physicochemical properties into pseudo nucleotide composition.Prediction of nucleosome positioning by the incorporation of frequencies and distributions of three different nucleotide segment lengths into a general pseudo k-tuple nucleotide composition.Imbalanced multi-label learning for identifying antimicrobial peptides and their functional types.iRNAm5C-PseDNC: identifying RNA 5-methylcytosine sites by incorporating physical-chemical properties into pseudo dinucleotide compositionPrediction of the aquatic toxicity of aromatic compounds to tetrahymena pyriformis through support vector regression.iATC-mHyb: a hybrid multi-label classifier for predicting the classification of anatomical therapeutic chemicals.iRNA-PseColl: Identifying the Occurrence Sites of Different RNA Modifications by Incorporating Collective Effects of Nucleotides into PseKNC.iRNA-AI: identifying the adenosine to inosine editing sites in RNA sequences.A novel feature ranking method for prediction of cancer stages using proteomics data.2L-PCA: a two-level principal component analyzer for quantitative drug design and its applications.MLACP: machine-learning-based prediction of anticancer peptides.UltraPse: A Universal and Extensible Software Platform for Representing Biological Sequences.Assessing the Performances of Protein Function Prediction Algorithms from the Perspectives of Identification Accuracy and False Discovery Rate.pLoc-mHum: predict subcellular localization of multi-location human proteins via general PseAAC to winnow out the crucial GO information.iPromoter-2L: a two-layer predictor for identifying promoters and their types by multi-window-based PseKNC.CarSite: identifying carbonylated sites of human proteins based on a one-sided selection resampling method.iMulti-HumPhos: a multi-label classifier for identifying human phosphorylated proteins using multiple kernel learning based support vector machines.MDD-carb: a combinatorial model for the identification of protein carbonylation sites with substrate motifs.ir-HSP: Improved Recognition of Heat Shock Proteins, Their Families and Sub-types Based On g-Spaced Di-peptide Features and Support Vector Machine.Improving succinylation prediction accuracy by incorporating the secondary structure via helix, strand and coil, and evolutionary information from profile bigrams.nifPred: Proteome-Wide Identification and Categorization of Nitrogen-Fixation Proteins of Diaztrophs Based on Composition-Transition-Distribution Features Using Support Vector Machine.Detecting Succinylation sites from protein sequences using ensemble support vector machine.Implications of Newly Identified Brain eQTL Genes and Their Interactors in Schizophrenia.Identification of Bacteriophage Virion Proteins Using Multinomial Naïve Bayes with g-Gap Feature Tree.
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iCar-PseCp: identify carbonylation sites in proteins by Monte Carlo sampling and incorporating sequence coupled effects into general PseAAC.
description
article científic
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article scientifique
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articolo scientifico
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artigo científico
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bilimsel makale
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scientific article published on 02 May 2016
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vedecký článok
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vetenskaplig artikel
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videnskabelig artikel
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vědecký článek
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iCar-PseCp: identify carbonyla ...... d effects into general PseAAC.
@en
iCar-PseCp: identify carbonyla ...... d effects into general PseAAC.
@nl
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label
iCar-PseCp: identify carbonyla ...... d effects into general PseAAC.
@en
iCar-PseCp: identify carbonyla ...... d effects into general PseAAC.
@nl
prefLabel
iCar-PseCp: identify carbonyla ...... d effects into general PseAAC.
@en
iCar-PseCp: identify carbonyla ...... d effects into general PseAAC.
@nl
P2093
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P356
P1433
P1476
iCar-PseCp: identify carbonyla ...... d effects into general PseAAC.
@en
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Bingxiang Liu
Jianhua Jia
P2860
P304
34558-34570
P356
10.18632/ONCOTARGET.9148
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P577
2016-05-02T00:00:00Z