about
Transcriptome Analysis in Domesticated Species: Challenges and StrategiesMicroarray experiments and factors which affect their reliabilityUtilizing de Bruijn graph of metagenome assembly for metatranscriptome analysisAn optimized protocol for generation and analysis of Ion Proton sequencing reads for RNA-SeqMost highly expressed protein-coding genes have a single dominant isoform.AllelicImbalance: an R/bioconductor package for detecting, managing, and visualizing allele expression imbalance data from RNA sequencingBenchmark analysis of algorithms for determining and quantifying full-length mRNA splice forms from RNA-seq dataData- and knowledge-based modeling of gene regulatory networks: an update.Multi-perspective quality control of Illumina RNA sequencing data analysis.Inter- and intra-species variation in genome-wide gene expression of Drosophila in response to parasitoid wasp attackTranscriptomics technologies.RNA sequencing and transcriptome arrays analyses show opposing results for alternative splicing in patient derived samplesOptimized Method for Robust Transcriptome Profiling of Minute Tissues Using Laser Capture Microdissection and Low-Input RNA-Seq.Identification of long non-coding RNA in the horse transcriptome.The impact of amplification on differential expression analyses by RNA-seqIsoSCM: improved and alternative 3' UTR annotation using multiple change-point inference.Sugarcane giant borer transcriptome analysis and identification of genes related to digestionDetection theory in identification of RNA-DNA sequence differences using RNA-sequencing.Integrated omics for the identification of key functionalities in biological wastewater treatment microbial communitiesAlternatively Spliced Homologous Exons Have Ancient Origins and Are Highly Expressed at the Protein Level.Tissue-Specific Evolution of Protein Coding Genes in Human and MouseTranscriptome analysis provides insights into the regulatory function of alternative splicing in antiviral immunity in grass carp (Ctenopharyngodon idella).Using mixtures of biological samples as process controls for RNA-sequencing experiments.TARDIS, a targeted RNA directional sequencing method for rare RNA discovery.Statistically based splicing detection reveals neural enrichment and tissue-specific induction of circular RNA during human fetal developmentIntegrative analysis of the Trypanosoma brucei gene expression cascade predicts differential regulation of mRNA processing and unusual control of ribosomal protein expressionErrors in RNA-Seq quantification affect genes of relevance to human disease.Gene activity in primary T cells infected with HIV89.6: intron retention and induction of genomic repeats.A catalogue of novel bovine long noncoding RNA across 18 tissues.On the design and prospects of direct RNA sequencing.Techniques and Approaches to Genetic Analyses in Nephrological Disorders.Modeling of RNA-seq fragment sequence bias reduces systematic errors in transcript abundance estimation.Genome maintenance and bioenergetics of the long-lived hypoxia-tolerant and cancer-resistant blind mole rat, Spalax: a cross-species analysis of brain transcriptome.Leveraging genome-wide datasets to quantify the functional role of the anti-Shine-Dalgarno sequence in regulating translation efficiency.Quantitative bacterial transcriptomics with RNA-seq.Screening the Molecular Framework Underlying Local Dendritic mRNA Translation.Combining Genome-Scale Experimental and Computational Methods To Identify Essential Genes in Rhodobacter sphaeroides.Methods, Tools and Current Perspectives in Proteogenomics.Detecting circular RNAs: bioinformatic and experimental challenges.Polyester: simulating RNA-seq datasets with differential transcript expression.
P2860
Q26766287-B46D37C2-C754-45CA-B9DA-9272239FC357Q26786123-C9F3C002-A87C-45EC-B772-4E92643FA178Q28828749-C87908B7-FB6F-4147-845A-FFB26B115874Q28833416-F8BDF87A-1258-4566-92AE-521D56F72C41Q30372321-7E33669F-35A8-46CE-967A-67112CDE8D09Q30970113-3AD41BDE-947E-46ED-9D7F-6DA8CEF4439AQ30991504-D4906D2A-2AB2-4C59-8C39-77D14CA59CC2Q31068983-71C41E73-4835-4711-B642-CE01435156A5Q31133867-932EC845-059E-4066-8F45-2A666ABD609AQ33608816-AF3A44B0-3B65-457E-80F8-50BB43D9D5AFQ33703532-FB83ED7A-82E9-4799-89FC-BCADE2A748E1Q33771657-5218110B-54CE-4DD2-9384-B8CC4E02BDE2Q33789983-0C79021A-0EB6-40DE-84BE-C4D067176BB2Q33868744-3885B104-403B-43F2-B6D8-C9EC3378B1F5Q34525647-67D730F9-790A-437F-80E8-43312AB324B5Q34761600-F8450F5F-4294-4398-8323-049B419110B1Q35113032-FDB46FAB-AAE0-40FE-BB28-C7A8CA199CB0Q35420623-555CA705-3FDC-44E9-8E93-AEA6BCEE7ADEQ35533194-FF0E347D-1E5A-4847-8870-9D4BBC8C81AFQ35659656-97A63B9A-89B2-4494-946D-22313F68E42CQ35677210-1C1E6A66-61A8-4D3D-9BE4-44BC88963077Q35739075-D7ADEA6F-5D40-4141-B6E7-6104BAE4CB8EQ35780469-42304EF3-C1B0-4786-BBE0-39D07240B806Q35826318-8B1C0F6F-4162-4392-BCC8-CD92AC518534Q35863369-4E143991-005F-4EB0-AEEF-4173B08F670FQ36000301-07C238A9-5C82-45C1-8412-5645B63B6B44Q36023606-1483E1A0-3F26-46A6-B33B-CC3D6C89E219Q36071452-5C087F11-1236-492C-A091-4525B4FB890FQ36203878-81FD314B-511B-43D6-AC2F-5B06311211AEQ36320223-FACB19D3-6F23-4F71-980F-C72B45E35764Q37032666-59079783-9E4C-4E67-862E-7929C8C87B5CQ37482304-11B6A4AD-AF99-46EA-93B8-7BABE37B9F71Q37487314-FD7F24D6-F06A-4605-BF09-1351D03468B8Q37637098-FA7CB19C-13BF-4E86-A095-77E67EA7FB14Q38284619-93418A4F-C59E-4AC9-A275-A3299669C747Q38558121-57101831-20E6-4FF3-99D2-5F75978D27D4Q38661204-F8B71B5D-CB46-4B1E-AF63-17489DB58530Q38812665-631732AE-E351-4499-8AE4-CA832053E94FQ38980353-643FCF07-E4E8-4EF0-909C-7B86526969F0Q40995562-95B39959-75AB-4B21-ABF7-78C0C231DB91
P2860
description
2014 nî lūn-bûn
@nan
2014 թուականին հրատարակուած գիտական յօդուած
@hyw
2014 թվականին 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
IVT-seq reveals extreme bias in RNA sequencing
@ast
IVT-seq reveals extreme bias in RNA sequencing
@en
IVT-seq reveals extreme bias in RNA sequencing
@en-gb
IVT-seq reveals extreme bias in RNA sequencing
@nl
type
label
IVT-seq reveals extreme bias in RNA sequencing
@ast
IVT-seq reveals extreme bias in RNA sequencing
@en
IVT-seq reveals extreme bias in RNA sequencing
@en-gb
IVT-seq reveals extreme bias in RNA sequencing
@nl
prefLabel
IVT-seq reveals extreme bias in RNA sequencing
@ast
IVT-seq reveals extreme bias in RNA sequencing
@en
IVT-seq reveals extreme bias in RNA sequencing
@en-gb
IVT-seq reveals extreme bias in RNA sequencing
@nl
P2093
P2860
P50
P3181
P356
P1433
P1476
IVT-seq reveals extreme bias in RNA sequencing
@en
P2093
Hannah Dueck
John B Hogenesch
Nicholas F Lahens
Rafael Irizarry
P2860
P2888
P3181
P356
10.1186/GB-2014-15-6-R86
P407
P50
P577
2014-01-01T00:00:00Z
P5875
P6179
1005699225