Empirical bayes analysis of sequencing-based transcriptional profiling without replicates. - Wikidata - wikimedia - TriplyDB

Empirical bayes analysis of sequencing-based transcriptional profiling without replicates.

Empirical bayes analysis of sequencing-based transcriptional profiling without replicates.

http://www.wikidata.org/entity/Q33748256

about

The analytical landscape of static and temporal dynamics in transcriptome data The transcriptome and proteome of the diatom Thalassiosira pseudonana reveal a diverse phosphorus stress response Transcriptomic analysis of metabolic function in the giant kelp, Macrocystis pyrifera, across depth and season Comparative studies of differential gene calling using RNA-Seq data.Transcripts and MicroRNAs Responding to Salt Stress in Musa acuminata Colla (AAA Group) cv. Berangan Roots.De novo assembly of Aureococcus anophagefferens transcriptomes reveals diverse responses to the low nutrient and low light conditions present during blooms.ExpressionPlot: a web-based framework for analysis of RNA-Seq and microarray gene expression data.On differential gene expression using RNA-Seq data Overview of available methods for diverse RNA-Seq data analyses.Statistical methods on detecting differentially expressed genes for RNA-seq data.Identifying reference genes with stable expression from high throughput sequence data.RNA sequencing of Populus x canadensis roots identifies key molecular mechanisms underlying physiological adaption to excess zinc Metatranscriptome analyses indicate resource partitioning between diatoms in the field.Bayesian Hierarchical Model for Differential Gene Expression Using RNA-seq Data Functional group-specific traits drive phytoplankton dynamics in the oligotrophic ocean.Getting the most out of RNA-seq data analysis.Eri1 regulates microRNA homeostasis and mouse lymphocyte development and antiviral function CEDER: accurate detection of differentially expressed genes by combining significance of exons using RNA-Seq.Conserved Transcriptional Responses to Nutrient Stress in Bloom-Forming Algae.Differential Expression Analysis in RNA-Seq by a Naive Bayes Classifier with Local Normalization.Variations in the non-coding transcriptome as a driver of inter-strain divergence and physiological adaptation in bacteria.Expression profiling of the bloom-forming cyanobacterium Nodularia CCY9414 under light and oxidative stress conditions.Identifying differentially expressed genes under heat stress and developing molecular markers in orchardgrass (Dactylis glomerata L.) through transcriptome analysis.

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P2860

Empirical bayes analysis of sequencing-based transcriptional profiling without replicates.

http://www.wikidata.org/entity/Q33748256

description

2010 nî lūn-bûn

@nan

2010 թուականի Նոյեմբերին հրատարակուած գիտական յօդուած

@hyw

2010 թվականի նոյեմբերին հրատարակված գիտական հոդված

@hy

2010年の論文

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2010年論文

@yue

2010年論文

@zh-hant

2010年論文

@zh-hk

2010年論文

@zh-mo

2010年論文

@zh-tw

2010年论文

@wuu

name

Empirical bayes analysis of se ...... profiling without replicates.

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Empirical bayes analysis of se ...... profiling without replicates.

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type

label

Empirical bayes analysis of se ...... profiling without replicates.

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Empirical bayes analysis of se ...... profiling without replicates.

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prefLabel

Empirical bayes analysis of se ...... profiling without replicates.

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Empirical bayes analysis of se ...... profiling without replicates.

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BMC Bioinformatics

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Empirical bayes analysis of se ...... profiling without replicates.

@en

P2093

Bethany D Jenkins

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

Leann P Whitney

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Mak A Saito

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Melissa Mercier

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Sonya T Dyhrman

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Tatiana A Rynearson

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P2860

Transcript length bias in RNA-seq data confounds systems biology

Bayesian model accounting for within-class biological variability in Serial Analysis of Gene Expression (SAGE).

Linear models and empirical bayes methods for assessing differential expression in microarray experiments

edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

Identification of microRNAs involved in the host response to enterovirus 71 infection by a deep sequencing approach

Substantial biases in ultra-short read data sets from high-throughput DNA sequencing

Studies of marine planktonic diatoms. I. Cyclotella nana Hustedt, and Detonula confervacea (cleve) Gran

Measuring differential gene expression by short read sequencing: quantitative comparison to 2-channel gene expression microarrays.

Dynamics of gene expression revealed by comparison of serial analysis of gene expression transcript profiles from yeast grown on two different carbon sources

Differential expression in SAGE: accounting for normal between-library variation.

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1471-2105-11-564

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10.1186/1471-2105-11-564

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11

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21080965

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3098101

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