Statistical models for RNA-seq data derived from a two-condition 48-replicate experiment.
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A Mechanistic Beta-Binomial Probability Model for mRNA Sequencing Data.SDEAP: a splice graph based differential transcript expression analysis tool for population data.Genomic responses to the socio-sexual environment in male Drosophila melanogaster exposed to conspecific rivals.Characterizing the reproductive transcriptomic correlates of acute dehydration in males in the desert-adapted rodent, Peromyscus eremicus.Elucidating tissue specific genes using the Benford distribution.Replicates, Read Numbers, and Other Important Experimental Design Considerations for Microbial RNA-seq Identified Using Bacillus thuringiensis DatasetsComparison of alternative approaches for analysing multi-level RNA-seq data.Genome-wide identification of soybean microRNA responsive to soybean cyst nematodes infection by deep sequencing.When and why does sex chromosome dosage compensation evolve?How many biological replicates are needed in an RNA-seq experiment and which differential expression tool should you use?Parasitoid gene expression changes after adaptation to symbiont-protected hosts.DEIsoM: a hierarchical Bayesian model for identifying differentially expressed isoforms using biological replicates.Microcystin-LR does not induce alterations to transcriptomic or metabolomic profiles of a model heterotrophic bacterium.Omics approaches to study gene regulatory networks for development in echinoderms.RNentropy: an entropy-based tool for the detection of significant variation of gene expression across multiple RNA-Seq experiments.Optimization of an RNA-Seq Differential Gene Expression Analysis Depending on Biological Replicate Number and Library Size.Silhouette Scores for Arbitrary Defined Groups in Gene Expression Data and Insights into Differential Expression Results.Broad distribution spectrum from Gaussian to power law appears in stochastic variations in RNA-seq data.
P2860
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P2860
Statistical models for RNA-seq data derived from a two-condition 48-replicate experiment.
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2015 nî lūn-bûn
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2015 թուականի Յուլիսին հրատարակուած գիտական յօդուած
@hyw
2015 թվականի հուլիսին հրատարակված գիտական հոդված
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2015年の論文
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2015年論文
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2015年論文
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2015年論文
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2015年論文
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2015年論文
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2015年论文
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name
Statistical models for RNA-seq data derived from a two-condition 48-replicate experiment.
@ast
Statistical models for RNA-seq data derived from a two-condition 48-replicate experiment.
@en
type
label
Statistical models for RNA-seq data derived from a two-condition 48-replicate experiment.
@ast
Statistical models for RNA-seq data derived from a two-condition 48-replicate experiment.
@en
prefLabel
Statistical models for RNA-seq data derived from a two-condition 48-replicate experiment.
@ast
Statistical models for RNA-seq data derived from a two-condition 48-replicate experiment.
@en
P2093
P2860
P50
P356
P1433
P1476
Statistical models for RNA-seq data derived from a two-condition 48-replicate experiment.
@en
P2093
Alexander Sherstnev
Marek Gierliński
Nicola Wrobel
Pietà Schofield
Vijender Singh
P2860
P304
P356
10.1093/BIOINFORMATICS/BTV425
P407
P50
P577
2015-07-23T00:00:00Z
P5875
P698
P818
1505.00588