Link prediction in drug-target interactions network using similarity indices
about
A simple mathematical approach to the analysis of polypharmacology and polyspecificity data.DDR: Efficient computational method to predict drug-target interactions using graph mining and machine learning approaches.Predicting potential drug-drug interactions on topological and semantic similarity features using statistical learning.Neural networks for link prediction in realistic biomedical graphs: a multi-dimensional evaluation of graph embedding-based approaches.Knowledge-based biomedical Data Science
P2860
Link prediction in drug-target interactions network using similarity indices
description
2017 nî lūn-bûn
@nan
2017 թուականի Յունուարին հրատարակուած գիտական յօդուած
@hyw
2017 թվականի հունվարին հրատարակված գիտական հոդված
@hy
2017年の論文
@ja
2017年論文
@yue
2017年論文
@zh-hant
2017年論文
@zh-hk
2017年論文
@zh-mo
2017年論文
@zh-tw
2017年论文
@wuu
name
Link prediction in drug-target interactions network using similarity indices
@ast
Link prediction in drug-target interactions network using similarity indices
@en
Link prediction in drug-target interactions network using similarity indices
@nl
type
label
Link prediction in drug-target interactions network using similarity indices
@ast
Link prediction in drug-target interactions network using similarity indices
@en
Link prediction in drug-target interactions network using similarity indices
@nl
prefLabel
Link prediction in drug-target interactions network using similarity indices
@ast
Link prediction in drug-target interactions network using similarity indices
@en
Link prediction in drug-target interactions network using similarity indices
@nl
P2093
P2860
P1433
P1476
Link prediction in drug-target interactions network using similarity indices
@en
P2093
Anna Korhonen
P2860
P2888
P356
10.1186/S12859-017-1460-Z
P407
P577
2017-01-17T00:00:00Z
P6179
1051074961