Mining breast cancer genes with a network based noise-tolerant approach
about
Fusion of genomic, proteomic and phenotypic data: the case of potyviruses.Identifying the gene signatures from gene-pathway bipartite network guarantees the robust model performance on predicting the cancer prognosis.EgoNet: identification of human disease ego-network modulesDetecting subnetwork-level dynamic correlations.Correcting for the study bias associated with protein-protein interaction measurements reveals differences between protein degree distributions from different cancer types.Systemic tracking of diagnostic function modules for post-menopausal osteoporosis in a differential co-expression network view.
P2860
Mining breast cancer genes with a network based noise-tolerant approach
description
2013 nî lūn-bûn
@nan
2013 թուականի Յունիսին հրատարակուած գիտական յօդուած
@hyw
2013 թվականի հունիսին հրատարակված գիտական հոդված
@hy
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
name
Mining breast cancer genes with a network based noise-tolerant approach
@ast
Mining breast cancer genes with a network based noise-tolerant approach
@en
type
label
Mining breast cancer genes with a network based noise-tolerant approach
@ast
Mining breast cancer genes with a network based noise-tolerant approach
@en
prefLabel
Mining breast cancer genes with a network based noise-tolerant approach
@ast
Mining breast cancer genes with a network based noise-tolerant approach
@en
P2860
P356
P1433
P1476
Mining breast cancer genes with a network based noise-tolerant approach
@en
P2093
Jingkai Yu
Yaling Nie
P2860
P2888
P356
10.1186/1752-0509-7-49
P577
2013-06-25T00:00:00Z
P5875
P6179
1047234080