Predicting drug-target interaction networks based on functional groups and biological features
about
Plant-mPLoc: a top-down strategy to augment the power for predicting plant protein subcellular localizationGenome-scale screening of drug-target associations relevant to Ki using a chemogenomics approachStructure and dynamics of molecular networks: a novel paradigm of drug discovery: a comprehensive reviewChemDes: an integrated web-based platform for molecular descriptor and fingerprint computationClassifying vulnerability to sleep deprivation using baseline measures of psychomotor vigilancePredicting functions of proteins in mouse based on weighted protein-protein interaction network and protein hybrid propertiesClassification and analysis of regulatory pathways using graph property, biochemical and physicochemical property, and functional propertyTwo birds with one stone? Possible dual-targeting H1N1 inhibitors from traditional Chinese medicinePrediction of protein domain with mRMR feature selection and analysisPrediction of drug-target interactions and drug repositioning via network-based inferenceA systematic prediction of multiple drug-target interactions from chemical, genomic, and pharmacological dataiGPCR-drug: a web server for predicting interaction between GPCRs and drugs in cellular networkingPotential Compounds for Oral Cancer Treatment: Resveratrol, Nimbolide, Lovastatin, Bortezomib, Vorinostat, Berberine, Pterostilbene, Deguelin, Andrographolide, and ColchicineMining Chemical Activity Status from High-Throughput Screening AssaysComputational Discovery of Putative Leads for Drug Repositioning through Drug-Target Interaction PredictioniEzy-drug: a web server for identifying the interaction between enzymes and drugs in cellular networkingPrediction of S-nitrosylation modification sites based on kernel sparse representation classification and mRMR algorithm.Computational Prediction of DrugTarget Interactions Using Chemical, Biological, and Network Features.In vitro transcriptomic prediction of hepatotoxicity for early drug discoverySimilarity-based prediction for Anatomical Therapeutic Chemical classification of drugs by integrating multiple data sources.Identification of amino acid propensities that are strong determinants of linear B-cell epitope using neural networks.Hepatitis C virus network based classification of hepatocellular cirrhosis and carcinomaImbalanced multi-modal multi-label learning for subcellular localization prediction of human proteins with both single and multiple sites.Multi-field-of-view framework for distinguishing tumor grade in ER+ breast cancer from entire histopathology slides.Drug target inference through pathway analysis of genomics data.Target identification and mechanism of action in chemical biology and drug discovery.Prediction and Analysis of Post-Translational Pyruvoyl Residue Modification Sites from Internal Serines in Proteins.Discovering the targets of drugs via computational systems biology.PredPPCrys: accurate prediction of sequence cloning, protein production, purification and crystallization propensity from protein sequences using multi-step heterogeneous feature fusion and selection.Exon skipping event prediction based on histone modifications.Discriminating between lysine sumoylation and lysine acetylation using mRMR feature selection and analysis.Classifying ten types of major cancers based on reverse phase protein array profiles.3D QSAR pharmacophore modeling, in silico screening, and density functional theory (DFT) approaches for identification of human chymase inhibitors.A comparative study of SMILES-based compound similarity functions for drug-target interaction predictionTargetNet: a web service for predicting potential drug-target interaction profiling via multi-target SAR models.Identification of compound-protein interactions through the analysis of gene ontology, KEGG enrichment for proteins and molecular fragments of compounds.Drug-target interaction prediction via class imbalance-aware ensemble learningFacPad: Bayesian sparse factor modeling for the inference of pathways responsive to drug treatment.Systems biology approaches for identifying adverse drug reactions and elucidating their underlying biological mechanisms.Improving compound-protein interaction prediction by building up highly credible negative samples.
P2860
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P2860
Predicting drug-target interaction networks based on functional groups and biological features
description
2010 nî lūn-bûn
@nan
2010 թուականի Մարտին հրատարակուած գիտական յօդուած
@hyw
2010 թվականի մարտին հրատարակված գիտական հոդված
@hy
2010年の論文
@ja
2010年論文
@yue
2010年論文
@zh-hant
2010年論文
@zh-hk
2010年論文
@zh-mo
2010年論文
@zh-tw
2010年论文
@wuu
name
Predicting drug-target interac ...... groups and biological features
@ast
Predicting drug-target interac ...... groups and biological features
@en
Predicting drug-target interac ...... groups and biological features
@nl
type
label
Predicting drug-target interac ...... groups and biological features
@ast
Predicting drug-target interac ...... groups and biological features
@en
Predicting drug-target interac ...... groups and biological features
@nl
prefLabel
Predicting drug-target interac ...... groups and biological features
@ast
Predicting drug-target interac ...... groups and biological features
@en
Predicting drug-target interac ...... groups and biological features
@nl
P2093
P2860
P1433
P1476
Predicting drug-target interac ...... groups and biological features
@en
P2093
Jian Zhang
Xiangyin Kong
Xiao-He Shi
Yu-Dong Cai
P2860
P356
10.1371/JOURNAL.PONE.0009603
P407
P577
2010-03-11T00:00:00Z