Browsing by Subject "annotation databases"

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Open Access
Development of a WEB application
(2011) Kaya, Koray Doğan
microRNAs, small non-coding RNA molecules with important roles in cellular machinery, target mRNAs for silencing by binding generally to their 3’ UTR sequences via partial base complementation. Thus, microRNAs with similar sequences also might exhibit expression and/or functional similarities. In this study, a modular tool, mESAdb (http://konulab.fen.bilkent.edu.tr/mirna/), was developed allowing for multivariate analysis of sequences and expression of microRNAs from multiple taxa. Its framework comprises PHP, JavaScript, packages in the R language, and a database storing mature microRNA sequences along with microRNA targets and selected expression data sets for human, mouse and zebrafish. mESAdb allows for: (i) mining of microRNA expression data sets for subsets of microRNAs selected manually or by a sequence motif; (ii) pair-wise multivariate analysis of expression data sets within and between taxa; and (iii) association of microRNA subsets with annotation databases, HuGE Navigator, KEGG and GO. mESAdb also permits user specified dataset upload for these analyses. Herein, utility of mESAdb was illustrated using different datasets and case studies. First, it was shown that microRNAs carrying the embryonic stem cell specific seed sequence, ‘AAGTGC’, were able to discriminate between normal and tumor tissues from hepatocellular carcinoma patients using dataset GSE10694. Second, mRNA targets of a set of liver specific microRNAs were annotated with human diseases based on HuGE Navigator. Third, the similarity between mouse and human tissue specificity of a given set of microRNAs was demonstrated. Forth, CHRNA5 targeting microRNAs were associated with estrogen receptor status in breast cancer using dataset GSE15885. Finally, a related tool under development for mRNA arrays planned for integration with mESAdb was presented.