Hierarchical clustering of high-throughput expression data based on general dependences.
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K-Profiles: A Nonlinear Clustering Method for Pattern Detection in High Dimensional Data.Nonlinear Network Reconstruction from Gene Expression Data Using Marginal Dependencies Measured by DCOL.Identifying heterogeneous subtypes of gastric cancer and subtype‑specific subpaths of microRNA‑target pathways.Missing value imputation for LC-MS metabolomics data by incorporating metabolic network and adduct ion relations.Neurite outgrowth resistance to rho kinase inhibitors in PC12 Adh cell.
P2860
Hierarchical clustering of high-throughput expression data based on general dependences.
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2013 nî lūn-bûn
@nan
2013 թուականի Յուլիսին հրատարակուած գիտական յօդուած
@hyw
2013 թվականի հուլիսին 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
Hierarchical clustering of high-throughput expression data based on general dependences.
@ast
Hierarchical clustering of high-throughput expression data based on general dependences.
@en
type
label
Hierarchical clustering of high-throughput expression data based on general dependences.
@ast
Hierarchical clustering of high-throughput expression data based on general dependences.
@en
prefLabel
Hierarchical clustering of high-throughput expression data based on general dependences.
@ast
Hierarchical clustering of high-throughput expression data based on general dependences.
@en
P2860
P356
P1476
Hierarchical clustering of high-throughput expression data based on general dependences.
@en
P2093
Hesen Peng
Tianwei Yu
P2860
P304
P356
10.1109/TCBB.2013.99
P577
2013-07-01T00:00:00Z