The 20 data sets comprised 10 LT and 10 Lde data sets, each of which contained muscle transcriptomes data at 35, 49, 63, 77, 91 days post-coitus and at 2, 28, 90, 120, 180 days post-natum [ 11].
We integrated a mouse muscle Bayesian Network and transcriptome data from the muscle of two inbred strains, LG/J and SM/J, with the results of QTL mapping of muscle weights in an advanced intercross [ 1] to nominate genes contributing to a 2-fold difference in muscle mass.
However, the discordance between the ChIP data and bodywall muscle transcriptome profiles also highlights the inherent flaws in experimental manipulation, current technologies employed for gene expression and ChIP studies, and bioinformatic treatment of the resulting data.
We also utilized the global muscle transcriptome as the background RNA expression data set, as misleading ontological enrichment P-values are yielded when a generic (genome-wide) reference data set is utilized.
Twenty-four sets of transcriptome data were generated for muscle and blood from six horses both BE and AE.
Currently, the MADMuscle database collects all transcriptome data sets related to muscle studies from the public repository Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/geo/) [ 13] of the National Center for Biotechnology Information (NCBI) at the National Institutes of Health (NIH).
Importantly, an increased Akt-mTOR signaling, as observed in atrophic COPD patients, may also represent an unsuccessful attempt trying to restore muscle mass [44], which agrees with ICU patient transcriptome data indicating a sustained protein synthesis similar to that in healthy controls in concert with a transcription program unable to compensate for enhanced protein breakdown [23], [45].
The CArGome Search Browser within the Smooth Muscle Cell Genome Browser was updated with the transcriptome data of primary SMCs isolated from colon and jejunum.
