Drug-target interaction prediction by random walk on the heterogeneous network.
about
Systems Medicine: The Application of Systems Biology Approaches for Modern Medical Research and Drug DevelopmentStructure and dynamics of molecular networks: a novel paradigm of drug discovery: a comprehensive reviewOptimizing drug–target interaction prediction based on random walk on heterogeneous networksDASPfind: new efficient method to predict drug–target interactionsPrediction of disease-related interactions between microRNAs and environmental factors based on a semi-supervised classifierA semi-supervised method for drug-target interaction prediction with consistency in networksPredicting Drug-Target Interactions for New Drug Compounds Using a Weighted Nearest Neighbor ProfileGraph theory enables drug repurposing--how a mathematical model can drive the discovery of hidden mechanisms of actionA systematic investigation of computation models for predicting Adverse Drug Reactions (ADRs)Inferring novel indications of approved drugs via a learning method with local and global consistencyLigand-target prediction by structural network biology using nAnnoLyzeIdentification of New Candidate Genes and Chemicals Related to Esophageal Cancer Using a Hybrid Interaction Network of Chemicals and ProteinsComputational Discovery of Putative Leads for Drug Repositioning through Drug-Target Interaction PredictionImproved genome-scale multi-target virtual screening via a novel collaborative filtering approach to cold-start problem.Predicting potential drug-drug interactions by integrating chemical, biological, phenotypic and network dataEffects of protein interaction data integration, representation and reliability on the use of network properties for drug target prediction.Drug-target interaction prediction by integrating chemical, genomic, functional and pharmacological data.COLLECTIVE PAIRWISE CLASSIFICATION FOR MULTI-WAY ANALYSIS OF DISEASE AND DRUG DATA.A review on machine learning principles for multi-view biological data integration.Comparative analysis of genes frequently regulated by drugs based on connectivity map transcriptome data.A novel network regularized matrix decomposition method to detect mutated cancer genes in tumour samples with inter-patient heterogeneity.HGPEC: a Cytoscape app for prediction of novel disease-gene and disease-disease associations and evidence collection based on a random walk on heterogeneous network.SuperPred: update on drug classification and target predictionA hybrid computational method for the discovery of novel reproduction-related genes.Network-based inference methods for drug repositioningTarget deconvolution of bioactive small molecules: the heart of chemical biology and drug discovery.Identifying novel associations between small molecules and miRNAs based on integrated molecular networks.A multiple kernel learning algorithm for drug-target interaction predictionTargetNet: a web service for predicting potential drug-target interaction profiling via multi-target SAR models.An eigenvalue transformation technique for predicting drug-target interaction.Drug combinatorics and side effect estimation on the signed human drug-target network.Inferring new indications for approved drugs via random walk on drug-disease heterogenous networks.Drug-target interaction prediction via class imbalance-aware ensemble learningSELF-BLM: Prediction of drug-target interactions via self-training SVMKATZLDA: KATZ measure for the lncRNA-disease association prediction.Global Prioritization of Disease Candidate Metabolites Based on a Multi-omics Composite Network.Deep mining heterogeneous networks of biomedical linked data to predict novel drug-target associations.WBSMDA: Within and Between Score for MiRNA-Disease Association prediction.A Bipartite Network-based Method for Prediction of Long Non-coding RNA-protein InteractionsAn integrated network platform for contextual prioritization of drugs and pathways
P2860
Q26781811-31B5D31D-F3E4-4B1C-80C8-8E82EE534F9BQ27008867-81ABF721-B4F7-43AD-BBA6-70EC5E5EE469Q27902299-BDEBB60C-5617-459A-945E-FDA78BBC28B3Q27902360-8B844A61-4956-4D51-B6CB-93E557CB64EBQ28482644-FDDDC572-8ACD-4FC5-9FFA-45EFD6BABEA7Q28487735-BFCB4814-E16E-4A31-9001-8719B3F1DB7EQ28534336-3EAA46AB-7C32-4305-9B68-6C818E76E754Q28538573-04ADCC3A-988B-4BCA-BFDE-951C28B92D2BQ28542690-F3327796-5758-4D0A-96D5-3F7638FC4DAFQ28543398-203BC814-D566-41F4-95F6-E2ABD1364689Q28545126-C78C947C-1AB6-400E-ABC8-EABE330405C2Q28548040-27B1974F-B4E6-4919-B7EB-D22BE6CE1C01Q28554438-C2E8EA26-997C-4405-9B74-6CAC746661D8Q28817549-69F3F941-5D82-4AEA-90C0-B1B9F4032426Q28817872-22CE2BB3-6B65-480A-B9D4-06F6A2AA2EB4Q30577213-ACE3EC3D-4426-48FD-BF58-8F47701A8361Q30705795-AC76BB4A-37FE-4B0F-8D50-88C96C3539BCQ31037303-13D5BE6F-C59C-47DF-AD7A-C13BD4572E77Q31151051-3FA119EC-B970-45B8-A076-ED8BF0FB2598Q33757949-11BBB215-7B30-4410-8F2D-593C976910FAQ33767347-581ED266-0AB1-4FE3-9FFE-EFDEA3AF9E5CQ33805002-505B000D-EF0D-45AF-A1CF-7771ABAD1C3CQ33860868-62917D8A-7964-4A79-8D6B-54A78C6397FFQ35174937-21513690-8C5D-48A3-9C7F-01CED297AC76Q35540850-998395C5-4DAB-464E-B746-882FD4DD2E07Q35652038-FF64FA9F-F4F1-45C4-8C28-0F41049601B7Q35703980-8AFE7F4F-6CEA-4878-AA61-EB86D8863361Q35901993-B39D0EAF-DB9D-4C55-8766-9D267CCC62CFQ36014246-839F54F3-FEE1-41F9-855D-3FE787D2D0C8Q36039506-CA6F7A7F-3847-489B-990E-5226F55D7302Q36104367-959BA30B-7BF2-42CC-8C20-562D461D9550Q36268650-CFA70977-9F23-4C32-A558-3541A7A775B9Q36268794-456D8717-C956-48BF-BDBB-9570FB25969EQ36278793-C95CA586-DBD2-4DA4-9C14-E1B9E1B558D5Q36291088-C2541025-EF20-4B43-A513-31E235E6B502Q36310177-469ACE62-FE43-44E0-B272-1BC832E74D9CQ36353609-D958C991-4AF0-45A1-980E-34E4AEB5E72DQ36583369-728A285D-932C-41F4-9C74-3E4C3FD68978Q36689907-776C6A44-F395-4CF8-9AFA-A008AFCD8302Q36746321-49587F80-86E3-409C-8B7D-CCD960882029
P2860
Drug-target interaction prediction by random walk on the heterogeneous network.
description
2012 nî lūn-bûn
@nan
2012年の論文
@ja
2012年学术文章
@wuu
2012年学术文章
@zh-cn
2012年学术文章
@zh-hans
2012年学术文章
@zh-my
2012年学术文章
@zh-sg
2012年學術文章
@yue
2012年學術文章
@zh
2012年學術文章
@zh-hant
name
Drug-target interaction prediction by random walk on the heterogeneous network.
@en
Drug-target interaction prediction by random walk on the heterogeneous network.
@nl
type
label
Drug-target interaction prediction by random walk on the heterogeneous network.
@en
Drug-target interaction prediction by random walk on the heterogeneous network.
@nl
prefLabel
Drug-target interaction prediction by random walk on the heterogeneous network.
@en
Drug-target interaction prediction by random walk on the heterogeneous network.
@nl
P2093
P2860
P356
P1433
P1476
Drug-target interaction prediction by random walk on the heterogeneous network.
@en
P2093
Gui-Ying Yan
Ming-Xi Liu
P2860
P304
P356
10.1039/C2MB00002D
P577
2012-04-26T00:00:00Z