github link
Accession IconGSE52037

Transcriptional override: a regulatory network model of indirect responses to modulations in microRNA expression (mRNA)

Organism Icon Homo sapiens
Sample Icon 18 Downloadable Samples
Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Submitter Supplied Information

Description
MicroRNAs are small non-coding molecules that have been shown to repress the translation of thousands of genes. Changes in microRNA expression in a variety of diseases, including cancer, are leading to the development of microRNAs as early indicators of disease, and to their potential use as therapeutic agents. A significant hurdle to the use of microRNAs as therapeutics is our inability to predict the molecular and cellular consequences of perturbations in the levels of specific microRNAs on targeted cells. While the direct gene (mRNA) targets of individual microRNAs can be computationally predicted and are often experimentally validated, assessing the indirect effects of microRNA variation remains a major challenge in molecular systems biology. We present experimental evidence for a computational model that quantifies the extent to which down-regulated transcriptional repressors contribute to the unanticipated upregulation of putative microRNA targets. An appreciation of the effects of these repressors may provide a more complete understanding of the indirect effects of microRNA dysregulation in diseases such as cancer, and to their successful clinical application.
PubMed ID
Total Samples
20
Submitter’s Institution
Alternate Accession IDs

Samples

Show of 0 Total Samples
Filter
Add/Remove
Accession Code
Title
Specimen part
Processing Information
Additional Metadata
No rows found
Loading...