about
RNA-Seq methods for transcriptome analysisDesign and computational analysis of single-cell RNA-sequencing experimentsSingle-cell Transcriptome Study as Big DataSingle-cell transcriptome sequencing: recent advances and remaining challengesImplications of Epigenetic Variability within a Cell Population for "Cell Type" ClassificationAnalytics for Metabolic EngineeringDefining cell types and states with single-cell genomicsDetecting Antigen-Specific T Cell Responses: From Bulk Populations to Single CellsCirculating RNAs as new biomarkers for detecting pancreatic cancerNanoscale monitoring of drug actions on cell membrane using atomic force microscopyAdvances and applications of single-cell sequencing technologiesAdvanced Applications of RNA Sequencing and ChallengesExperimental approaches to identify small RNAs and their diverse roles in bacteria--what we have learnt in one decade of MicA researchCellTree: an R/bioconductor package to infer the hierarchical structure of cell populations from single-cell RNA-seq data.A microfluidic platform enabling single-cell RNA-seq of multigenerational lineages.Snake Genome Sequencing: Results and Future ProspectsTumour Heterogeneity: The Key Advantages of Single-Cell AnalysisSingle-cell gene expression profiling and cell state dynamics: collecting data, correlating data points and connecting the dotsSingle cells get together: High-resolution approaches to study the dynamics of early mouse developmentMultiplexed, targeted profiling of single-cell proteomes and transcriptomes in a single reactionMicrofluidics for genome-wide studies involving next generation sequencing.Highly multiplexed targeted DNA sequencing from single nucleiDB-AT: a 2015 update to the Full-parasites database brings a multitude of new transcriptomic data for apicomplexan parasites.BASiCS: Bayesian Analysis of Single-Cell Sequencing DataSingle-cell SNP analyses and interpretations based on RNA-Seq data for colon cancer research.Integrated single cell data analysis reveals cell specific networks and novel coactivation markersLow-cost, Low-bias and Low-input RNA-seq with High Experimental Verifiability based on Semiconductor SequencingUnderstanding RNA modifications: the promises and technological bottlenecks of the 'epitranscriptome'.Cancer metastasis through the prism of epithelial-to-mesenchymal transition in circulating tumor cells.Ribosome profiling reveals the what, when, where and how of protein synthesisSingle-cell analyses of transcriptional heterogeneity during drug tolerance transition in cancer cells by RNA sequencing.Non-coding RNA regulation in pathogenic bacteria located inside eukaryotic cells.The impact of amplification on differential expression analyses by RNA-seqBioXpress: an integrated RNA-seq-derived gene expression database for pan-cancer analysis.Cell type-specific gene expression profiling in brain tissue: comparison between TRAP, LCM and RNA-seqQuantitative single cell gene expression profiling in the avian embryo.Deep Sequencing in Microdissected Renal Tubules Identifies Nephron Segment-Specific TranscriptomesSINCERA: A Pipeline for Single-Cell RNA-Seq Profiling AnalysisIsolation of intact astrocytes from the optic nerve head of adult mice.Laser capture microdissection of intestinal tissue from sea bass larvae using an optimized RNA integrity assay and validated reference genes.
P2860
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P2860
description
2014 nî lūn-bûn
@nan
2014 թուականի Օգոստոսին հրատարակուած գիտական յօդուած
@hyw
2014 թվականի օգոստոսին հրատարակված գիտական հոդված
@hy
2014年の論文
@ja
2014年論文
@yue
2014年論文
@zh-hant
2014年論文
@zh-hk
2014年論文
@zh-mo
2014年論文
@zh-tw
2014年论文
@wuu
name
Single-cell RNA-seq: advances and future challenges
@ast
Single-cell RNA-seq: advances and future challenges
@en
Single-cell RNA-seq: advances and future challenges
@nl
type
label
Single-cell RNA-seq: advances and future challenges
@ast
Single-cell RNA-seq: advances and future challenges
@en
Single-cell RNA-seq: advances and future challenges
@nl
prefLabel
Single-cell RNA-seq: advances and future challenges
@ast
Single-cell RNA-seq: advances and future challenges
@en
Single-cell RNA-seq: advances and future challenges
@nl
P2860
P3181
P356
P1476
Single-cell RNA-seq: advances and future challenges
@en
P2093
Antoine-Emmanuel Saliba
Stanislaw A. Gorski
P2860
P304
P3181
P356
10.1093/NAR/GKU555
P407
P577
2014-08-01T00:00:00Z