Deep mining heterogeneous networks of biomedical linked data to predict novel drug-target associations.
about
DDR: Efficient computational method to predict drug-target interactions using graph mining and machine learning approaches.Prediction of drug-pathway interaction pairs with a disease-combined LSA-PU-KNN method.Biosignature Discovery for Substance Use Disorders Using Statistical Learning.Modeling polypharmacy side effects with graph convolutional networks.
P2860
Deep mining heterogeneous networks of biomedical linked data to predict novel drug-target associations.
description
2017 nî lūn-bûn
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2017年の論文
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2017年学术文章
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name
Deep mining heterogeneous netw ...... ovel drug-target associations.
@ast
Deep mining heterogeneous netw ...... ovel drug-target associations.
@en
type
label
Deep mining heterogeneous netw ...... ovel drug-target associations.
@ast
Deep mining heterogeneous netw ...... ovel drug-target associations.
@en
prefLabel
Deep mining heterogeneous netw ...... ovel drug-target associations.
@ast
Deep mining heterogeneous netw ...... ovel drug-target associations.
@en
P2860
P356
P1433
P1476
Deep mining heterogeneous netw ...... ovel drug-target associations.
@en
P2093
Nansu Zong
Victoria Ngo
P2860
P304
P356
10.1093/BIOINFORMATICS/BTX160
P407
P577
2017-04-18T00:00:00Z