RNA-Seq analysis to capture the transcriptome landscape of a single cell. - Wikidata - awgldk - TriplyDB

RNA-Seq analysis to capture the transcriptome landscape of a single cell.

RNA-Seq analysis to capture the transcriptome landscape of a single cell.

http://www.wikidata.org/entity/Q33536986

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Current challenges in the bioinformatics of single cell genomics.Quartz-Seq: a highly reproducible and sensitive single-cell RNA sequencing method, reveals non-genetic gene-expression heterogeneity Single cell genomics: advances and future perspectives Mechanistic and structural insight into the functional dichotomy between IL-2 and IL-15 Evaluation and consequences of heterogeneity in the circulating tumor cell compartment Single-cell Transcriptome Study as Big Data Single-cell technologies are revolutionizing the approach to rare cells Single-cell technologies to study the immune system The applications of single-cell genomics Genomic analysis at the single-cell level Heterogeneity in immune responses: from populations to single cells Single-cell RNA-seq: advances and future challenges The ability of inner-cell-mass cells to self-renew as embryonic stem cells is acquired following epiblast specification Single cell transcriptomics: methods and applications Building an RNA Sequencing Transcriptome of the Central Nervous System Maternal LSD1/KDM1A is an essential regulator of chromatin and transcription landscapes during zygotic genome activation Transcriptome characterization by RNA-Seq reveals the involvement of the complement components in noise-traumatized rat cochleae Prdm14 promotes germline fate and naive pluripotency by repressing FGF signalling and DNA methylation ENU mutagenesis reveals that Notchless homolog 1 (Drosophila) affects Cdkn1a and several members of the Wnt pathway during murine pre-implantation development RNA Sequencing and Analysis Using single nuclei for RNA-seq to capture the transcriptome of postmortem neurons Single-cell RNA-seq transcriptome analysis of linear and circular RNAs in mouse preimplantation embryos.RNA-sequencing from single nuclei.Stochastic profiling of transcriptional regulatory heterogeneities in tissues, tumors and cultured cells A simple add-on microfluidic appliance for accurately sorting small populations of cells with high fidelity.Cell-to-cell expression variability followed by signal reinforcement progressively segregates early mouse lineages.Novel PRD-like homeodomain transcription factors and retrotransposon elements in early human development.Improving reliability and absolute quantification of human brain microarray data by filtering and scaling probes using RNA-Seq.Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells.Logic programming to infer complex RNA expression patterns from RNA-seq data.Targeted expression of μ-opioid receptors in a subset of striatal direct-pathway neurons restores opiate reward.Stella modulates transcriptional and endogenous retrovirus programs during maternal-to-zygotic transition.Quantitative dynamics of triacylglycerol accumulation in microalgae populations at single-cell resolution revealed by Raman microspectroscopy Quantitative assessment of single-cell RNA-sequencing methods.Mining of public sequencing databases supports a non-dietary origin for putative foreign miRNAs: underestimated effects of contamination in NGS.Microfluidic single-cell whole-transcriptome sequencing.Deep sequencing-based transcriptome profiling analysis of bacteria-challenged Lateolabrax japonicus reveals insight into the immune-relevant genes in marine fish.Histone demethylases UTX and JMJD3 are required for NKT cell development in mice Single-neuron transcriptome and methylome sequencing for epigenomic analysis of aging.Cancer metastasis through the prism of epithelial-to-mesenchymal transition in circulating tumor cells.

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RNA-Seq analysis to capture the transcriptome landscape of a single cell.

http://www.wikidata.org/entity/Q33536986

description

2010 nî lūn-bûn

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2010 թուականի Փետրուարին հրատարակուած գիտական յօդուած

@hyw

2010 թվականի փետրվարին հրատարակված գիտական հոդված

@hy

2010年の論文

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2010年論文

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2010年論文

@zh-hant

2010年論文

@zh-hk

2010年論文

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2010年論文

@zh-tw

2010年论文

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name

RNA-Seq analysis to capture the transcriptome landscape of a single cell.

@ast

RNA-Seq analysis to capture the transcriptome landscape of a single cell.

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RNA-Seq analysis to capture the transcriptome landscape of a single cell.

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type

label

RNA-Seq analysis to capture the transcriptome landscape of a single cell.

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RNA-Seq analysis to capture the transcriptome landscape of a single cell.

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RNA-Seq analysis to capture the transcriptome landscape of a single cell.

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prefLabel

RNA-Seq analysis to capture the transcriptome landscape of a single cell.

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RNA-Seq analysis to capture the transcriptome landscape of a single cell.

@en

RNA-Seq analysis to capture the transcriptome landscape of a single cell.

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Nature Protocols

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RNA-Seq analysis to capture the transcriptome landscape of a single cell.

@en

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Bin Li

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Catalin Barbacioru

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Ellen Nordman

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Fuchou Tang

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Kaiqin Lao

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Nanlan Xu

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Vladimir I Bashkirov

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P2860

Mapping and quantifying mammalian transcriptomes by RNA-Seq

RNA exosome depletion reveals transcription upstream of active human promoters

Noise in gene expression: origins, consequences, and control.

RNA-Seq: a revolutionary tool for transcriptomics

Nature, nurture, or chance: stochastic gene expression and its consequences

The transcriptional landscape of the yeast genome defined by RNA sequencing

Determination of tag density required for digital transcriptome analysis: application to an androgen-sensitive prostate cancer model

RNA-seq: an assessment of technical reproducibility and comparison with gene expression arrays

Single-cell expression profiling of human epidermal stem and transit-amplifying cells: Lrig1 is a regulator of stem cell quiescence

An improved single-cell cDNA amplification method for efficient high-density oligonucleotide microarray analysis

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516-535

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10.1038/NPROT.2009.236

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3

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5

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1004430683

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20203668

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3847604

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