Counting individual DNA molecules by the stochastic attachment of diverse labels.
about
Single-cell transcriptome sequencing: recent advances and remaining challengesGenomic analysis at the single-cell levelLibrary construction for next-generation sequencing: overviews and challenges.Single cell transcriptomics: methods and applicationsSources of PCR-induced distortions in high-throughput sequencing data setsA cost effective 5΄ selective single cell transcriptome profiling approach with improved UMI design.The promise and challenge of high-throughput sequencing of the antibody repertoire.Counting absolute numbers of molecules using unique molecular identifiers.MT-Toolbox: improved amplicon sequencing using molecule tags.Detection of ultra-rare mutations by next-generation sequencing.Quantitative single-cell RNA-seq with unique molecular identifiers.Facilitated sequence counting and assembly by template mutagenesis.Turning single cells into microarrays by super-resolution barcoding.Hierarchical molecular tagging to resolve long continuous sequences by massively parallel sequencingGenetic measurement of memory B-cell recall using antibody repertoire sequencing.An efficient and sensitive method for preparing cDNA libraries from scarce biological samples.Expression profiling. Combinatorial labeling of single cells for gene expression cytometry.Digital RNA sequencing minimizes sequence-dependent bias and amplification noise with optimized single-molecule barcodesSiNG-PCRseq: Accurate inter-sequence quantification achieved by spiking-in a neighbor genome for competitive PCR amplicon sequencing.Benefits and Challenges with Applying Unique Molecular Identifiers in Next Generation Sequencing to Detect Low Frequency Mutations.Ultrasensitive single-genome sequencing: accurate, targeted, next generation sequencing of HIV-1 RNA.Application of Stochastic Labeling with Random-Sequence Barcodes for Simultaneous Quantification and Sequencing of Environmental 16S rRNA GenesThe workflow of single-cell expression profiling using quantitative real-time PCR.Single molecule molecular inversion probes for targeted, high-accuracy detection of low-frequency variationDeepSNVMiner: a sequence analysis tool to detect emergent, rare mutations in subsets of cell populationsProtein kinase D regulates positive selection of CD4(+) thymocytes through phosphorylation of SHP-1.Batch effects and the effective design of single-cell gene expression studies.Molecular indexing enables quantitative targeted RNA sequencing and reveals poor efficiencies in standard library preparationsSingle-cell mRNA quantification and differential analysis with Census.Digital encoding of cellular mRNAs enabling precise and absolute gene expression measurement by single-molecule counting.Massive parallel-sequencing-based hydroxyl radical probing of RNA accessibilityHigh-throughput, multiparameter analysis of single cells.Methods, Challenges and Potentials of Single Cell RNA-seq.Assaying the epigenome in limited numbers of cellsSpatially resolved transcriptome profiling in model plant species.Effect of method of deduplication on estimation of differential gene expression using RNA-seq.MtDNA As a Cancer Marker: A Finally Closed Chapter?Revealing the vectors of cellular identity with single-cell genomics.High-throughput sequencing of the T-cell receptor repertoire: pitfalls and opportunities.Detection of prostate cancer-specific transcripts in extracellular vesicles isolated from post-DRE urine.
P2860
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P2860
Counting individual DNA molecules by the stochastic attachment of diverse labels.
description
2011 nî lūn-bûn
@nan
2011 թուականի Մայիսին հրատարակուած գիտական յօդուած
@hyw
2011 թվականի մայիսին հրատարակված գիտական հոդված
@hy
2011年の論文
@ja
2011年論文
@yue
2011年論文
@zh-hant
2011年論文
@zh-hk
2011年論文
@zh-mo
2011年論文
@zh-tw
2011年论文
@wuu
name
Counting individual DNA molecules by the stochastic attachment of diverse labels.
@ast
Counting individual DNA molecules by the stochastic attachment of diverse labels.
@en
type
label
Counting individual DNA molecules by the stochastic attachment of diverse labels.
@ast
Counting individual DNA molecules by the stochastic attachment of diverse labels.
@en
prefLabel
Counting individual DNA molecules by the stochastic attachment of diverse labels.
@ast
Counting individual DNA molecules by the stochastic attachment of diverse labels.
@en
P2093
P2860
P356
P1476
Counting individual DNA molecules by the stochastic attachment of diverse labels.
@en
P2093
Glenn K Fu
Pei-Hua Wang
Stephen P A Fodor
P2860
P304
P356
10.1073/PNAS.1017621108
P407
P577
2011-05-11T00:00:00Z