Predicting drug-target interactions using probabilistic matrix factorization.
about
Systems Medicine: The Application of Systems Biology Approaches for Modern Medical Research and Drug DevelopmentImplications of the small number of distinct ligand binding pockets in proteins for drug discovery, evolution and biochemical functionA multi-label approach to target prediction taking ligand promiscuity into accountAdverse drug reaction prediction using scores produced by large-scale drug-protein target docking on high-performance computing machinesNeighborhood Regularized Logistic Matrix Factorization for Drug-Target Interaction PredictionImproved genome-scale multi-target virtual screening via a novel collaborative filtering approach to cold-start problem.Computational prediction of virus-human protein-protein interactions using embedding kernelized heterogeneous data.BalestraWeb: efficient online evaluation of drug-target interactions.Comprehensive prediction of drug-protein interactions and side effects for the human proteome.Systems biology approaches for identifying adverse drug reactions and elucidating their underlying biological mechanisms.In silico methods for drug repurposing and pharmacologyA Perspective on Implementing a Quantitative Systems Pharmacology Platform for Drug Discovery and the Advancement of Personalized Medicine.Quantitative Structure-activity Relationship (QSAR) Models for Docking Score Correction.Drug-target interaction prediction via chemogenomic space: learning-based methods.Drug-target interaction prediction: databases, web servers and computational models.COMPUTING THERAPY FOR PRECISION MEDICINE: COLLABORATIVE FILTERING INTEGRATES AND PREDICTS MULTI-ENTITY INTERACTIONS.Insights into the Modulation of Dopamine Transporter Function by Amphetamine, Orphenadrine, and Cocaine BindingVB-MK-LMF: fusion of drugs, targets and interactions using variational Bayesian multiple kernel logistic matrix factorization.The revolution of personalized psychiatry: will technology make it happen sooner?Utilizing random Forest QSAR models with optimized parameters for target identification and its application to target-fishing server.Drug knowledge bases and their applications in biomedical informatics research.Connecting Neuronal Cell Protective Pathways and Drug Combinations in a Huntington's Disease Model through the Application of Quantitative Systems Pharmacology.Web-based drug repurposing tools: a survey.Pioneering topological methods for network-based drug-target prediction by exploiting a brain-network self-organization theory.Prediction of Protein-compound Binding Energies from Known Activity Data: Docking-score-based Method and its Applications.DeepDTA: deep drug-target binding affinity prediction
P2860
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P2860
Predicting drug-target interactions using probabilistic matrix factorization.
description
2013 nî lūn-bûn
@nan
2013年の論文
@ja
2013年論文
@yue
2013年論文
@zh-hant
2013年論文
@zh-hk
2013年論文
@zh-mo
2013年論文
@zh-tw
2013年论文
@wuu
2013年论文
@zh
2013年论文
@zh-cn
name
Predicting drug-target interactions using probabilistic matrix factorization.
@en
Predicting drug-target interactions using probabilistic matrix factorization.
@nl
type
label
Predicting drug-target interactions using probabilistic matrix factorization.
@en
Predicting drug-target interactions using probabilistic matrix factorization.
@nl
prefLabel
Predicting drug-target interactions using probabilistic matrix factorization.
@en
Predicting drug-target interactions using probabilistic matrix factorization.
@nl
P2093
P2860
P356
P1476
Predicting drug-target interactions using probabilistic matrix factorization.
@en
P2093
Feizhuo Hu
Murat Can Cobanoglu
Zoltán N Oltvai
P2860
P304
P356
10.1021/CI400219Z
P50
P577
2013-12-10T00:00:00Z