about
Single cell genomics: advances and future perspectivesIVT-seq reveals extreme bias in RNA sequencingNext generation sequencing technology and genomewide data analysis: Perspectives for retinal researchSingle-cell transcriptome sequencing: recent advances and remaining challengesRibosome profiling: a Hi-Def monitor for protein synthesis at the genome-wide scaleTargeted RNA-sequencing with competitive multiplex-PCR amplicon librariesEffects of Gene Dose, Chromatin, and Network Topology on Expression in Drosophila melanogasterA survey of best practices for RNA-seq data analysisStandardization and quality management in next-generation sequencingAccurate and predictive antibody repertoire profiling by molecular amplification fingerprintingAn evolutionarily conserved long noncoding RNA TUNA controls pluripotency and neural lineage commitmentRNA Sequencing and AnalysisPotential role of multiple carbon fixation pathways during lipid accumulation in Phaeodactylum tricornutumUsing single nuclei for RNA-seq to capture the transcriptome of postmortem neuronsToward reliable biomarker signatures in the age of liquid biopsies - how to standardize the small RNA-Seq workflowDesign of RNA splicing analysis null models for post hoc filtering of Drosophila head RNA-Seq data with the splicing analysis kit (Spanki)Improving reliability and absolute quantification of human brain microarray data by filtering and scaling probes using RNA-Seq.Reducing bias in RNA sequencing data: a novel approach to compute counts.Normalization of RNA-sequencing data from samples with varying mRNA levelsNavigating and mining modENCODE data.Deciphering global signal features of high-throughput array data from cancers.Normalization of RNA-seq data using factor analysis of control genes or samplesHigh-throughput spatial mapping of single-cell RNA-seq data to tissue of origin.PDEGEM: Modeling non-uniform read distribution in RNA-Seq dataBASiCS: Bayesian Analysis of Single-Cell Sequencing DataStatistical models for RNA-seq data derived from a two-condition 48-replicate experiment.Processing, visualising and reconstructing network models from single-cell data.Comparison of normalization and differential expression analyses using RNA-Seq data from 726 individual Drosophila melanogaster.Synthetic spike-in standards improve run-specific systematic error analysis for DNA and RNA sequencing.Synthetic spike-in standards for high-throughput 16S rRNA gene amplicon sequencing.Knowledge about the presence or absence of miRNA isoforms (isomiRs) can successfully discriminate amongst 32 TCGA cancer typesAccelerated Evolution of Developmentally Biased Genes in the Tetraphenic Ant Cardiocondyla obscurior.Stella modulates transcriptional and endogenous retrovirus programs during maternal-to-zygotic transition.Quantitative assessment of single-cell RNA-sequencing methods.Quality control on the frontier.XSAnno: a framework for building ortholog models in cross-species transcriptome comparisons.Transcriptomics technologies.ToNER: A tool for identifying nucleotide enrichment signals in feature-enriched RNA-seq dataSingle-cell RNA-sequencing of the brain.Profiling of drought-responsive microRNA and mRNA in tomato using high-throughput sequencing
P2860
Q21563353-60BEF6FA-9DEE-4093-A857-9168CB364171Q21999522-903BF9D2-D382-4ED0-B8E1-487CCF062036Q26746206-0A25F999-365A-49F7-B6B0-50A855D91E5CQ26767451-787E1AA5-7223-404A-B805-E71F592B56CEQ26822785-A1FF7CC7-19AD-4A09-8B65-B33D69B7D104Q27302929-DD6F15FE-AE9B-469D-9C29-5451674A2B59Q27307966-1614AB68-4B5B-40AF-9486-351EF3474CBBQ28071394-80AA2B4E-186E-4C3B-8758-F586D8E9C04FQ28077041-D9A99FFA-136F-4288-8AD5-9D221C1F42B6Q28274314-DB92576B-4D25-482B-9DE9-13067CEC2D38Q28585984-603DD81C-2DD8-4521-BB93-7D1C2060B914Q28602964-697A7F29-7BC7-41B8-A52C-0F3A86728012Q28727495-BF168723-70C7-40FE-BC58-FBD402A0D0A5Q30277319-2EEB4FAE-E94E-4974-B526-14ED0CA424DEQ30363613-DA872ADB-4736-4344-AFCF-73DF0E8E3A4DQ30691324-B31C3FF2-BB82-4A6E-B479-A78595DC3F4DQ30763070-07243C0E-FD1B-43B0-A7DD-F4981241A276Q30763179-8621DAAB-2316-4F6F-A60A-509A08CA0E58Q30768621-999E1094-473E-466B-BD4B-009567AC8829Q30779594-99179728-3911-4C45-98B3-2F286ACA3358Q30792298-BF9A9752-8C86-4D2F-8728-41194ADD469CQ30844396-6453DE6C-574E-4CB7-92B0-FB6986D81E29Q30930642-E20CE213-67FE-432D-BD58-0D68B12DB85EQ30965995-184669CB-0A2A-4E11-948E-9CE953E635DCQ30976555-CADF386D-95EF-4DCB-A1DC-FBFB44C70374Q30982380-AE4A504F-83D0-4A3D-B50D-9516B2F30677Q31024831-1480D333-225F-4E31-96CD-0707995420DAQ31035102-0E0239EA-04CA-49B5-8355-3207602EC539Q31079862-5EB94E6D-45B1-4BBA-B051-DF2CAAEE4ACEQ33557389-FE95BFDC-E5BB-4859-9318-65D6587F23A0Q33557718-6ED7FAEE-BC65-4380-9F1C-83419F742CB0Q33590734-E9B9B377-FA84-4678-A214-BFD912238670Q33603026-BA2AEB17-C3D4-4818-BD99-FF3CE992B432Q33619848-954CF828-2981-4D5B-9239-44B424E08526Q33663633-70683E83-1818-41B5-A0E0-9822CFD959DAQ33669240-E6BE2A40-7F12-42D4-BDBD-AFDE5181DD6DQ33703532-6F6340B4-409D-4D81-B81D-EC1992B5FF53Q33728579-CB56D1E3-80DB-461C-9B30-4106C7CA031DQ33780520-D5F22893-79DE-4542-924A-F54C8F82E12FQ33837485-22AACDDC-4B57-4EC0-AE99-4EA46CE6F81D
P2860
description
2011 nî lūn-bûn
@nan
2011 թուականի Օգոստոսին հրատարակուած գիտական յօդուած
@hyw
2011 թվականի օգոստոսին 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
Synthetic spike-in standards for RNA-seq experiments.
@ast
Synthetic spike-in standards for RNA-seq experiments.
@en
type
label
Synthetic spike-in standards for RNA-seq experiments.
@ast
Synthetic spike-in standards for RNA-seq experiments.
@en
prefLabel
Synthetic spike-in standards for RNA-seq experiments.
@ast
Synthetic spike-in standards for RNA-seq experiments.
@en
P2093
P2860
P356
P1433
P1476
Synthetic spike-in standards for RNA-seq experiments.
@en
P2093
Brian Oliver
Carrie A Davis
Felix Schlesinger
Lichun Jiang
Marc Salit
P2860
P304
P356
10.1101/GR.121095.111
P577
2011-08-04T00:00:00Z