CAERUS: predicting CAncER oUtcomeS using relationship between protein structural information, protein networks, gene expression data, and mutation data.
about
Integrative approaches for finding modular structure in biological networksStructural bioinformatics of the interactome.Predicting cancer prognosis using functional genomics data sets.Integration of somatic mutation, expression and functional data reveals potential driver genes predictive of breast cancer survival.Reproducible quantification of cancer-associated proteins in body fluids using targeted proteomics.A network module-based method for identifying cancer prognostic signaturesMono-isotope Prediction for Mass Spectra Using Bayes Network.A systems biology strategy to identify molecular mechanisms of action and protein indicators of traumatic brain injury.CARDIO-PRED: an in silico tool for predicting cardiovascular-disorder associated proteinsAdvances in computational approaches for prioritizing driver mutations and significantly mutated genes in cancer genomesIntegration of proteomics into systems biology of cancer.Protein interaction networks in medicine and disease.Cancer associated proteins in blood plasma: Determining normal variation.Gene Prioritization by Integrated Analysis of Protein Structural and Network Topological Properties for the Protein-Protein Interaction Network of Neurological Disorders.An iron regulatory gene signature in breast cancer: more than a prognostic genetic profile?Using protein interaction database and support vector machines to improve gene signatures for prediction of breast cancer recurrence.Elucidating the genotype-phenotype relationships and network perturbations of human shared and specific disease genes from an evolutionary perspective.Network-based sub-network signatures unveil the potential for acute myeloid leukemia therapy.Proteomic approaches in biomarker discovery: new perspectives in cancer diagnostics.
P2860
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P2860
CAERUS: predicting CAncER oUtcomeS using relationship between protein structural information, protein networks, gene expression data, and mutation data.
description
2011 nî lūn-bûn
@nan
2011 թուականի Մարտին հրատարակուած գիտական յօդուած
@hyw
2011 թվականի մարտին հրատարակված գիտական հոդված
@hy
2011年の論文
@ja
2011年論文
@yue
2011年論文
@zh-hant
2011年論文
@zh-hk
2011年論文
@zh-mo
2011年論文
@zh-tw
2011年论文
@wuu
name
CAERUS: predicting CAncER oUtc ...... ssion data, and mutation data.
@ast
CAERUS: predicting CAncER oUtc ...... ssion data, and mutation data.
@en
type
label
CAERUS: predicting CAncER oUtc ...... ssion data, and mutation data.
@ast
CAERUS: predicting CAncER oUtc ...... ssion data, and mutation data.
@en
prefLabel
CAERUS: predicting CAncER oUtc ...... ssion data, and mutation data.
@ast
CAERUS: predicting CAncER oUtc ...... ssion data, and mutation data.
@en
P2860
P1476
CAERUS: predicting CAncER oUtc ...... ssion data, and mutation data.
@en
P2093
B F Francis Ouellette
Kelvin Xi Zhang
P2860
P304
P356
10.1371/JOURNAL.PCBI.1001114
P577
2011-03-31T00:00:00Z