Differential and trajectory methods for time course gene expression data. - Wikidata - awgldk - TriplyDB

Differential and trajectory methods for time course gene expression data.

Differential and trajectory methods for time course gene expression data.

http://www.wikidata.org/entity/Q30989514

about

Post hoc pattern matching: assigning significance to statistically defined expression patterns in single channel microarray data.Bayesian models and meta analysis for multiple tissue gene expression data following corticosteroid administration.Identification of potential new treatment response markers and therapeutic targets using a Gaussian process-based method in lapatinib insensitive breast cancer models.Dynamics of dendritic cell maturation are identified through a novel filtering strategy applied to biological time-course microarray replicates Identification of Cancer Related Genes Using a Comprehensive Map of Human Gene Expression Transcriptional profiling of multiple sclerosis: towards improved diagnosis and treatment.Acetaminophen modulates the transcriptional response to recombinant interferon-beta.Time series expression analyses using RNA-seq: a statistical approach.

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P2860

Differential and trajectory methods for time course gene expression data.

http://www.wikidata.org/entity/Q30989514

description

2005 nî lūn-bûn

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2005 թուականի Մայիսին հրատարակուած գիտական յօդուած

@hyw

2005 թվականի մայիսին հրատարակված գիտական հոդված

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2005年の論文

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2005年論文

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2005年論文

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2005年論文

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2005年論文

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2005年論文

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2005年论文

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name

Differential and trajectory methods for time course gene expression data.

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Differential and trajectory methods for time course gene expression data.

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Differential and trajectory methods for time course gene expression data.

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Differential and trajectory methods for time course gene expression data.

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Differential and trajectory methods for time course gene expression data.

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Differential and trajectory methods for time course gene expression data.

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Differential and trajectory methods for time course gene expression data.

@en

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Arpad Kelemen

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Bamidele Tayo

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Xueya Cai

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Yulan Liang

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P2860

Significance analysis of microarrays applied to the ionizing radiation response

'Gene shaving' as a method for identifying distinct sets of genes with similar expression patterns

Multivariate search for differentially expressed gene combinations

Assessing gene significance from cDNA microarray expression data via mixed models

A Bayesian framework for the analysis of microarray expression data: regularized t -test and statistical inferences of gene changes

Singular value decomposition for genome-wide expression data processing and modeling

Analysis of variance for gene expression microarray data

SVDMAN--singular value decomposition analysis of microarray data.

Principal component analysis for clustering gene expression data.

Nonparametric methods for identifying differentially expressed genes in microarray data.

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10.1093/BIOINFORMATICS/BTI465

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