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Functional interpretation of miRNA expression data is currently done in a three step procedure: select differentially expressed miRNAs, find their target genes, and carry out gene set overrepresentation analysis Nevertheless, major limitations of this approach have already been described at the gene level, while some newer arise in the miRNA scenario.Here, we propose an enhanced methodology that builds on the well-established gene set analysis paradigm.

Cross-talk between competitive endogenous RNAs (ceRNAs) through shared miRNAs represents a novel layer of gene regulation that plays important roles in the physiology and development of cancers. However, a global view of their system-level properties across various types of cancers is still unknown. Here, we constructed the mRNA related ceRNA-ceRNA interaction landscape across 20 cancer types by systematically analyzing molecular profiles of 5203 tumors and miRNA regulations.

Long non-coding RNAs (lncRNAs) are functional non-translated molecules greater than 200 nt. Their roles are diverse and they are usually involved in transcriptional regulation. LncRNAs still remain largely uninvestigated in plants with few exceptions. Experimentally validated plant lncRNAs have been shown to regulate important agronomic traits such as phosphate starvation response, flowering time and interaction with symbiotic organisms, making them of great interest in plant biology and in breeding.

MicroRNAs are increasingly being appreciated as critical players in human diseases, and questions concerning the role of microRNAs arise in many areas of biomedical research. There are several manually curated databases of microRNA-disease associations gathered from the biomedical literature; however, it is difficult for curators of these databases to keep up with the explosion of publications in the microRNA-disease field.