about
Statistical assessment of crosstalk enrichment between gene groups in biological networksHierarchy of gene expression data is predictive of future breast cancer outcomeNetwork based integrated analysis of phenotype-genotype data for prioritization of candidate symptom genesMining breast cancer genes with a network based noise-tolerant approachIdentifying the gene signatures from gene-pathway bipartite network guarantees the robust model performance on predicting the cancer prognosis.Disease gene interaction pathways: a potential framework for how disease genes associate by disease-risk modules.Network enrichment analysis: extension of gene-set enrichment analysis to gene networks.Text mining in cancer gene and pathway prioritization.Chapter 15: disease gene prioritization.Dovetailing biology and chemistry: integrating the Gene Ontology with the ChEBI chemical ontology.A systematic in silico mining of the mechanistic implications and therapeutic potentials of estrogen receptor (ER)-α in breast cancer.Identification of ULK1 as a novel biomarker involved in miR-4487 and miR-595 regulation in neuroblastoma SH-SY5Y cell autophagyIntegrating network, sequence and functional features using machine learning approaches towards identification of novel Alzheimer genesNetwork-based analysis identifies epigenetic biomarkers of esophageal squamous cell carcinoma progression.Network analysis in the identification of special mechanisms between small cell lung cancer and non-small cell lung cancerA network-based maximum link approach towards MS identifies potentially important roles for undetected ARRB1/2 and ACTB in liver cancer progression.Comparative network-based recovery analysis and proteomic profiling of neurological changes in valproic acid-treated mice.FunCoup 3.0: database of genome-wide functional coupling networks.GenePANDA-a novel network-based gene prioritizing tool for complex diseasesHow advancement in biological network analysis methods empowers proteomics.Identification of novel caspase/autophagy-related gene switch to cell fate decisions in breast cancers.Identification of microRNA-regulated autophagic pathways in plant lectin-induced cancer cell death.A large-scale benchmark of gene prioritization methodsClass-paired Fuzzy SubNETs: A paired variant of the rank-based network analysis family for feature selection based on protein complexes.Network-based identification of key proteins involved in apoptosis and cell cycle regulation.Identification of novel kinase inhibitors by targeting a kinase-related apoptotic protein-protein interaction network in HeLa cells.Evaluating predictive performance of network biomarkers with network structures.Predicting potential cancer genes by integrating network properties, sequence features and functional annotations.MaxLink: network-based prioritization of genes tightly linked to a disease seed set.
P2860
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P2860
description
2009 nî lūn-bûn
@nan
2009 թուականի Դեկտեմբերին հրատարակուած գիտական յօդուած
@hyw
2009 թվականի դեկտեմբերին հրատարակված գիտական հոդված
@hy
2009年の論文
@ja
2009年論文
@yue
2009年論文
@zh-hant
2009年論文
@zh-hk
2009年論文
@zh-mo
2009年論文
@zh-tw
2009年论文
@wuu
name
Network-based Identification of novel cancer genes.
@ast
Network-based Identification of novel cancer genes.
@en
type
label
Network-based Identification of novel cancer genes.
@ast
Network-based Identification of novel cancer genes.
@en
prefLabel
Network-based Identification of novel cancer genes.
@ast
Network-based Identification of novel cancer genes.
@en
P2860
P1476
Network-based Identification of novel cancer genes.
@en
P2093
Gabriel Ostlund
Mats Lindskog
P2860
P304
P356
10.1074/MCP.M900227-MCP200
P577
2009-12-03T00:00:00Z