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Decoding transcriptional programs governing transcriptomic diversity across human multiple tissues is a major challenge in bioinformatics.
Further their expression in multiple tissues is clearly not limited to regulation by muscle-specific transcription factors like myod.
Nonetheless, in general the significance of somatic mosaicism usually remains under-appreciated and performance of detailed postmortem follow-up of the aberrations in multiple tissues is done only rarely.
Overlap analysis between multiple tissues is more desired, while these overlaps are very limited due to the high noise-to-signal ratio of microarray.
TF and their target genes interact in a temporal and tissue dependent manner, so the examination of networks spanning multiple tissues is critical to highlight interactions that could otherwise be unknown from individual tissue analysis [ 48].
Evidence for the participation of mesenchymal stromal cells (MSCs) in the tissue repair process across multiple tissues is overwhelming and their role in reparative disorders is clearly demonstrated, as is the involvement of a number of specific signaling pathways.
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While phylogenetic analysis of transcriptomes of the same tissue is usually congruent with the species tree, the controversy emerges when multiple tissues are included, that is, whether species from the same tissue are clustered together, or different tissues from the same species are clustered together.
Multiple tissues were dissected from the mice.
The multiple tissues were used for the isolation of total RNAs.
Moreover, the mRNA expression patterns of CDT2 and INTS7 in multiple tissues were inconsistent.
An appropriate control gene for comparing human and chimpanzee expression across multiple tissues was defined by steady expression between and within species as well as across tissues.
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