Ensemble positive unlabeled learning for disease gene identification
about
Microbial community pattern detection in human body habitats via ensemble clustering framework.Positive-unlabeled learning for the prediction of conformational B-cell epitopes.SGFSC: speeding the gene functional similarity calculation based on hash tablesUsing contrast patterns between true complexes and random subgraphs in PPI networks to predict unknown protein complexes.In silico prediction of novel therapeutic targets using gene-disease association data.Computationally predicting protein-RNA interactions using only positive and unlabeled examples.Prediction of drug-pathway interaction pairs with a disease-combined LSA-PU-KNN method.Systematic interrogation of diverse Omic data reveals interpretable, robust, and generalizable transcriptomic features of clinically successful therapeutic targets.
P2860
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P2860
Ensemble positive unlabeled learning for disease gene identification
description
2014 nî lūn-bûn
@nan
2014 թուականի Մայիսին հրատարակուած գիտական յօդուած
@hyw
2014 թվականի մայիսին հրատարակված գիտական հոդված
@hy
2014年の論文
@ja
2014年論文
@yue
2014年論文
@zh-hant
2014年論文
@zh-hk
2014年論文
@zh-mo
2014年論文
@zh-tw
2014年论文
@wuu
name
Ensemble positive unlabeled learning for disease gene identification
@ast
Ensemble positive unlabeled learning for disease gene identification
@en
type
label
Ensemble positive unlabeled learning for disease gene identification
@ast
Ensemble positive unlabeled learning for disease gene identification
@en
prefLabel
Ensemble positive unlabeled learning for disease gene identification
@ast
Ensemble positive unlabeled learning for disease gene identification
@en
P2093
P2860
P1433
P1476
Ensemble positive unlabeled learning for disease gene identification
@en
P2093
Chee-Keong Kwoh
Hon-Nian Chua
See-Kiong Ng
P2860
P304
P356
10.1371/JOURNAL.PONE.0097079
P407
P577
2014-05-09T00:00:00Z