Combining gene signatures improves prediction of breast cancer survival.
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Survival prediction based on compound covariate under Cox proportional hazard modelsBoosting the concordance index for survival data--a unified framework to derive and evaluate biomarker combinations.What does matrix metalloproteinase-1 expression in patients with breast cancer really tell us?Long non-coding RNAs differentially expressed between normal versus primary breast tumor tissues disclose converse changes to breast cancer-related protein-coding genes.Systematic assessment of prognostic gene signatures for breast cancer shows distinct influence of time and ER status.Integrative analysis of survival-associated gene sets in breast cancer.GeneSigDB: a manually curated database and resource for analysis of gene expression signaturesLow Concordance between Gene Expression Signatures in ER Positive HER2 Negative Breast Carcinoma Could Impair Their Clinical Application.Stromal genes add prognostic information to proliferation and histoclinical markers: a basis for the next generation of breast cancer gene signatures.Gene expression profile analysis of t1 and t2 breast cancer reveals different activation pathwaysLINC00472 expression is regulated by promoter methylation and associated with disease-free survival in patients with grade 2 breast cancer.Hybrid method for prediction of metastasis in breast cancer patients using gene expression signals.Machine-learning prediction of cancer survival: a retrospective study using electronic administrative records and a cancer registry.An iron regulatory gene signature in breast cancer: more than a prognostic genetic profile?Gene signature combinations improve prognostic stratification of multiple myeloma patients.Using protein interaction database and support vector machines to improve gene signatures for prediction of breast cancer recurrence.Combined analysis of vascular invasion, grade, HER2 and Ki67 expression identifies early breast cancer patients with questionable benefit of systemic adjuvant therapy.Survival analysis by penalized regression and matrix factorization.Genes and functions from breast cancer signatures.A 35-gene signature discriminates between rapidly- and slowly-progressing glioblastoma multiforme and predicts survival in known subtypes of the cancer.Machine Learning With K-Means Dimensional Reduction for Predicting Survival Outcomes in Patients With Breast Cancer
P2860
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P2860
Combining gene signatures improves prediction of breast cancer survival.
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
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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
Combining gene signatures improves prediction of breast cancer survival.
@ast
Combining gene signatures improves prediction of breast cancer survival.
@en
type
label
Combining gene signatures improves prediction of breast cancer survival.
@ast
Combining gene signatures improves prediction of breast cancer survival.
@en
prefLabel
Combining gene signatures improves prediction of breast cancer survival.
@ast
Combining gene signatures improves prediction of breast cancer survival.
@en
P2860
P50
P1433
P1476
Combining gene signatures improves prediction of breast cancer survival.
@en
P2093
Arnoldo Frigessi
P2860
P304
P356
10.1371/JOURNAL.PONE.0017845
P407
P50
P577
2011-03-10T00:00:00Z