about
Overdispersed logistic regression for SAGE: modelling multiple groups and covariatesThe transcriptome of Toxoplasma gondii.Modeling transcriptome based on transcript-sampling dataDiscoverySpace: an interactive data analysis application.Increasing the efficiency of SAGE adaptor ligation by directed ligation chemistryModeling SAGE tag formation and its effects on data interpretation within a Bayesian framework.Large-scale production of SAGE libraries from microdissected tissues, flow-sorted cells, and cell linesUnexpected observations after mapping LongSAGE tags to the human genomeDeep analysis of cellular transcriptomes - LongSAGE versus classic MPSSA score system for quality evaluation of RNA sequence tags: an improvement for gene expression profilingUsing reads to annotate the genome: influence of length, background distribution, and sequence errors on prediction capacity.
P2860
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P2860
description
2001 nî lūn-bûn
@nan
2001 թուականի Սեպտեմբերին հրատարակուած գիտական յօդուած
@hyw
2001 թվականի սեպտեմբերին հրատարակված գիտական հոդված
@hy
2001年の論文
@ja
2001年論文
@yue
2001年論文
@zh-hant
2001年論文
@zh-hk
2001年論文
@zh-mo
2001年論文
@zh-tw
2001年论文
@wuu
name
Detecting the impact of sequencing errors on SAGE data.
@ast
Detecting the impact of sequencing errors on SAGE data.
@en
type
label
Detecting the impact of sequencing errors on SAGE data.
@ast
Detecting the impact of sequencing errors on SAGE data.
@en
prefLabel
Detecting the impact of sequencing errors on SAGE data.
@ast
Detecting the impact of sequencing errors on SAGE data.
@en
P356
P1433
P1476
Detecting the impact of sequencing errors on SAGE data
@en
P2093
P304
P356
10.1093/BIOINFORMATICS/17.9.840
P407
P577
2001-09-01T00:00:00Z