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- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2016.2
- 수록면
- 225 - 243 (19page)
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Thanks to recent advance of next generation sequencing techniques, RNA-seq enabled to have an unprecedented opportunity to identify transcript variants with isofom diversity and allelic imbalance (Anders et al, 2012) by different transcriptional rates. To date, it is well known that those features might be associated with the aberrant patterns of disease complexity such as tissue (Anders and Huber, 2010; Anders et al, 2012; Nariai et al., 2014) specific differential expression at isoform levels or tissue specific allelic imbalance in mal-functionality of disease processes, etc. Nevertheless, the knowledge of post-transcriptional modification and AI in transcriptomic and genomic areas has been little known in the traditional platforms due to the limitation of technology and insufficient resolution. We here stress the potential of isoform variability and allelic specific expression that are relevant to the abnormality of disease mechanisms in transcriptional genetic regulatory networks. In addition, we systematically review how robust Bayesian approaches in RNA-seq have been developed and utilized in this regard in the field.
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참고문헌 (78)
참고문헌 신청
[학술지(정기간행물)] - Anders, S. / 2010 / Di erential expression analysis for sequence count data / Genome Biology 11 : 106 ~
[학술지(정기간행물)] - Anders, S. / 2013 / Count-based di erential expression analysis of RNA sequencing data using R and Bioconductor / Nature Protocols 8 : 1765 ~ 1786
[학술지(정기간행물)] - Anders, S. / 2012 / Detecting di erential usage of exons from RNA-seq data / Genome Research 22 : 2008 ~ 2017
[학술지(정기간행물)] - Aryee, M. J. / 2009 / An improved empirical bayes approach to estimating di erential gene expression in microarray time-course data : BETR(Bayesian Estimation of Temporal Regulation) / BMC Bioinformatics 10 : 409 ~
[학술지(정기간행물)] - Bar-Joseph, Z. / 2012 / Studying and modelling dynamic biological processes using time-series gene expression data. Nature Reviews / Genetics 13 : 552 ~ 564
[학술지(정기간행물)] - Anders, S. / 2013 / Count-based di erential expression analysis of RNA sequencing data using R and Bioconductor / Nature Protocols 8 : 1765 ~ 1786
[학술지(정기간행물)] - Anders, S. / 2012 / Detecting di erential usage of exons from RNA-seq data / Genome Research 22 : 2008 ~ 2017
[학술지(정기간행물)] - Aryee, M. J. / 2009 / An improved empirical bayes approach to estimating di erential gene expression in microarray time-course data : BETR(Bayesian Estimation of Temporal Regulation) / BMC Bioinformatics 10 : 409 ~
[학술지(정기간행물)] - Bar-Joseph, Z. / 2012 / Studying and modelling dynamic biological processes using time-series gene expression data. Nature Reviews / Genetics 13 : 552 ~ 564
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UCI(KEPA) : I410-ECN-0101-2018-041-001377599