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@ARTICLE{Usadel:132999,
author = {Usadel, Björn and Fernie, A.R.},
title = {{T}he plant transcriptome—from integrating observations
to models},
journal = {Frontiers in Plant Physiology},
volume = {4},
number = {48},
issn = {1664-462X},
address = {Lausanne},
publisher = {Frontiers Media83580},
reportid = {FZJ-2013-01568},
pages = {1-3},
year = {2013},
abstract = {Transcriptomes as assessed by either microarrays or
next-generation sequencing have produced a hitherto
unprecedented data flood regarding transcript identity and
levels in plant systems. Microarray data has been
extensively used over the last 15 years or so and evaluation
of the data thus produced has progressed well beyond early
statistically quality evaluation and descriptive lists to a
mature science whereby gene networks and cascades have been
able to provide mechanistic insight. The development of
sensitive quantitative PCR for lowly expressed genes such as
transcription factors has additionally allowed another layer
of complexity to be accessed and the modeling of
transcription factor expression with that of target genes
has met considerable success. Yet more recently, data
emanating from RNAseq studies have greatly improved the
coverage of transcript profiling. That said, this technology
further compounded transcriptome analysis by making it
possible to identify differentially spliced transcripts etc.
In this research topic we would like to provide an “on the
fly” portrait of the use of either microarray or RNAseq
based datasets in contemporary Plant Systems Biology.},
cin = {IBG-2},
ddc = {580},
cid = {I:(DE-Juel1)IBG-2-20101118},
pnm = {242 - Sustainable Bioproduction (POF2-242)},
pid = {G:(DE-HGF)POF2-242},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000329584400001},
doi = {10.3389/fpls.2013.00048},
url = {https://juser.fz-juelich.de/record/132999},
}