Epilepsy is one of the most frequent neurological disorders. Recently, the regulation of microRNAs was found to be associated with epilepsy, but the molecular mechanism by which microRNA influences epilepsy process remains to be unveiled and the development of microRNA-based therapy requires more intensive research. In this study, five microRNAs with potential relevance to epilepsy were initially chosen: miR-132, miR-146a, miR-181a, miR-34a, and miR-124. Twenty-five children who were patients with epilepsy were selected as subjects to obtain tissue samples for the study.
MicroRNAs (miRNAs) are major post-transcriptional regulators of gene expression. In an attempt to gain insights into miRNAs at the macroevolutionary level, we performed a systematic analysis of miRNAs in six model organisms based on their evolutionary rates. First, we calculated their miRNA evolutionary rates, and found that they did not correlate with the complexity of the organisms.
This report describes the miRQuest - a novel middleware available in a Web server that allows the end user to do the miRNA research in a user-friendly way. It is known that there are many prediction tools for microRNA (miRNA) identification that use different programming languages and methods to realize this task. It is difficult to understand each tool and apply it to diverse datasets and organisms available for miRNA analysis. miRQuest can easily be used by biologists and researchers with limited experience with bioinformatics.
Chronic lymphocytic leukemia (CLL) is a disease that involves progressive accumulation of nonfunctioning lymphocytes and has a low cure rate. There is an urgent requirement to determine the molecular mechanism underlying this disease in order to improve the early diagnosis and treatment of CLL. In this study, genes differentially expressed between CLL samples and age-matched controls were identified using microRNA (miRNA) and mRNA expression profiles. Differentially expressed (DE) miRNA targets were predicted by combining five algorithms.