Characterization of bovine miRNAs by sequencing and bioinformatics analysis

Background  

MicroRNAs (miRNAs) are a family of ~22 nucleotide small RNA molecules which regulate gene expression by fully or partially binding to their complementary sequences in mRNAs or promoters. A large number of miRNAs and their expression patterns have been reported in human, mouse and rat. However, miRNAs and their expression patterns in live stock species such as beef cattle are not well studied.     

Detecting microRNA activity from gene expression data

Background  

MicroRNAs (miRNAs) are non-coding RNAs that regulate gene expression by binding to the messenger RNA (mRNA) of protein coding genes. They control gene expression by either inhibiting translation or inducing mRNA degradation. A number of computational techniques have been developed to identify the targets of miRNAs. In this study we used predicted miRNA-gene interactions to analyse mRNA gene expression microarray data to predict miRNAs associated with particular diseases or conditions.     

miRAS: a data processing system for miRNA expression profiling study

Background  

The study of microRNAs (miRNAs) is attracting great considerations. Recent studies revealed that miRNAs play as important regulators of gene expression and some even as cancer players or inhibitors. Many studies try to discover new miRNAs and reveal the miRNA expression profile in cancer using a SAGE-based total RNA clone method. However, the data processing of this method is labor-intensive with several different biological databases and more than ten data processing steps involved.     

New miRNA labeling method for bead-based quantification

Background  

microRNAs (miRNAs) are small single-stranded non-coding RNAs that act as crucial regulators of gene expression. Different methods have been developed for miRNA expression profiling in order to better understand gene regulation in normal and pathological conditions. miRNAs expression values obtained from large scale methodologies such as microarrays still need a validation step with alternative technologies.     

Computational and transcriptional evidence for microRNAs in the honey bee genome

Background  

Non-coding microRNAs (miRNAs) are key regulators of gene expression in eukaryotes. Insect miRNAs help regulate the levels of proteins involved with development, metabolism, and other life history traits. The recently sequenced honey bee genome provides an opportunity to detect novel miRNAs in both this species and others, and to begin to infer the roles of miRNAs in honey bee development.     

Prediction and preliminary validation of oncogene regulation by miRNAs

Background  

MicroRNAs (miRNAs) are one of the most abundant groups of regulatory genes in multicellular organisms, playing important roles in many fundamental cellular processes. More than four hundred miRNAs have been identified in humans and the deregulation of miRNA expression has been also shown in many cancers. Despite the postulated involvement of miRNAs in tumourigenesis, there are only a few examples where an oncogene or a tumour suppressor has been identified as a miRNA target.     

Identification of baboon microRNAs expressed in liver and lymphocytes

Background  

MicroRNAs (miRNAs) are small noncoding RNAs (~22 nucleotides) that regulate gene expression by cleaving mRNAs or inhibiting translation. The baboon is a well-characterized cardiovascular disease model; however, no baboon miRNAs have been identified. Evidence indicates that the baboon and human genomes are highly conserved; based on this conservation, we hypothesized that comparative genomic methods could be used to identify baboon miRNAs.     

TAM: A method for enrichment and depletion analysis of a microRNA category in a list of microRNAs

Background  

MicroRNAs (miRNAs) are a class of important gene regulators. The number of identified miRNAs has been increasing dramatically in recent years. An emerging major challenge is the interpretation of the genome-scale miRNA datasets, including those derived from microarray and deep-sequencing. It is interesting and important to know the common rules or patterns behind a list of miRNAs, (i.e. the deregulated miRNAs resulted from an experiment of miRNA microarray or deep-sequencing).