Comparative meta-analysis of prognostic gene signatures for late-stage ovarian cancer - Wikidata - awgldk - TriplyDB

Comparative meta-analysis of prognostic gene signatures for late-stage ovarian cancer

Comparative meta-analysis of prognostic gene signatures for late-stage ovarian cancer

http://www.wikidata.org/entity/Q26859166

about

Stroma-associated master regulators of molecular subtypes predict patient prognosis in ovarian cancer.Orchestrating high-throughput genomic analysis with Bioconductor A reproducible approach to high-throughput biological data acquisition and integration Más-o-menos: a simple sign averaging method for discrimination in genomic data analysis.Cross-study validation for the assessment of prediction algorithms.Genome-driven integrated classification of breast cancer validated in over 7,500 samples.OvMark: a user-friendly system for the identification of prognostic biomarkers in publically available ovarian cancer gene expression datasets.Single Gene Prognostic Biomarkers in Ovarian Cancer: A Meta-Analysis.Characterization of twenty-five ovarian tumour cell lines that phenocopy primary tumours.Leveraging global gene expression patterns to predict expression of unmeasured genes Machine Learning Meta-analysis of Large Metagenomic Datasets: Tools and Biological Insights.Risk prediction for late-stage ovarian cancer by meta-analysis of 1525 patient samples.Prediction of Possible Biomarkers and Novel Pathways Conferring Risk to Post-Traumatic Stress Disorder Distance in cancer gene expression from stem cells predicts patient survival.E2F4 Program Is Predictive of Progression and Intravesical Immunotherapy Efficacy in Bladder Cancer Optimized Prediction of Extreme Treatment Outcomes in Ovarian Cancer.Characteristics of 10-year survivors of high-grade serous ovarian carcinoma.Genetic and molecular changes in ovarian cancer.NUAK1 (ARK5) Is Associated with Poor Prognosis in Ovarian Cancer.MARCKS contributes to stromal cancer-associated fibroblast activation and facilitates ovarian cancer metastasis.Preoperative red cell distribution width and neutrophil-to-lymphocyte ratio predict survival in patients with epithelial ovarian cancer The Prognostic 97 Chemoresponse Gene Signature in Ovarian Cancer.Patient-specific driver gene prediction and risk assessment through integrated network analysis of cancer omics profiles.Personalized dynamic prediction of death according to tumour progression and high-dimensional genetic factors: Meta-analysis with a joint model.The Doppelgänger Effect: Hidden Duplicates in Databases of Transcriptome Profiles.Open access to large scale datasets is needed to translate knowledge of cancer heterogeneity into better patient outcomes.The expression of miRNAs is associated with tumour genome instability and predicts the outcome of ovarian cancer patients treated with platinum agents.SIRT1 deacetylates KLF4 to activate Claudin-5 transcription in ovarian cancer cells.Integrative multi-platform meta-analysis of gene expression profiles in pancreatic ductal adenocarcinoma patients for identifying novel diagnostic biomarkers.Next generation sequencing of pancreatic ductal adenocarcinoma: right or wrong?Data and Statistical Methods To Analyze the Human Microbiome.Training replicable predictors in multiple studies.

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Comparative meta-analysis of prognostic gene signatures for late-stage ovarian cancer

http://www.wikidata.org/entity/Q26859166

description

2014 nî lūn-bûn

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2014 թուականի Ապրիլին հրատարակուած գիտական յօդուած

@hyw

2014 թվականի ապրիլին հրատարակված գիտական հոդված

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2014年の論文

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2014年論文

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2014年論文

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2014年論文

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2014年論文

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2014年論文

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2014年论文

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name

Comparative meta-analysis of prognostic gene signatures for late-stage ovarian cancer

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Comparative meta-analysis of prognostic gene signatures for late-stage ovarian cancer

@en

Comparative meta-analysis of prognostic gene signatures for late-stage ovarian cancer

@nl

type

label

Comparative meta-analysis of prognostic gene signatures for late-stage ovarian cancer

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Comparative meta-analysis of prognostic gene signatures for late-stage ovarian cancer

@en

Comparative meta-analysis of prognostic gene signatures for late-stage ovarian cancer

@nl

prefLabel

Comparative meta-analysis of prognostic gene signatures for late-stage ovarian cancer

@ast

Comparative meta-analysis of prognostic gene signatures for late-stage ovarian cancer

@en

Comparative meta-analysis of prognostic gene signatures for late-stage ovarian cancer

@nl

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Journal of the National Cancer Institute

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Comparative meta-analysis of prognostic gene signatures for late-stage ovarian cancer

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Benjamin Frederick Ganzfried

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Christoph Bernau

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Curtis Huttenhower

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Giovanni Parmigiani

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Jie Ding

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Levi Waldron

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Mahnaz Ahmadifar

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Michael Birrer

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Svitlana Tyekucheva

http://www.w3.org/2001/XMLSchema#string

Thomas Risch

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P2860

Bioconductor: open software development for computational biology and bioinformatics

Why Your New Cancer Biomarker May Never Work: Recurrent Patterns and Remarkable Diversity in Biomarker Failures

Scientific research in the age of omics: the good, the bad, and the sloppy

Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles.

Public availability of published research data in high-impact journals

Integrated genomic analyses of ovarian carcinoma

Cancer statistics, 2012

Repeatability of published microarray gene expression analyses

Angiogenic mRNA and microRNA gene expression signature predicts a novel subtype of serous ovarian cancer

Adjusting batch effects in microarray expression data using empirical Bayes methods

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151070

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10.1093/JNCI/DJU049

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5

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106

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Benjamin Haibe-Kains

Aedin C Culhane

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2014-04-03T00:00:00Z

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261374934

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24700801

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4580554

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