| Summary: | 碩士 === 國立成功大學 === 電機工程學系 === 104 === MicroRNAs (miRNAs) are functional RNA molecules which play important roles in post-transcriptional regulation. miRNAs regulate their targets by repressing translation or inducing degradation of target mRNAs. Several databases have been constructed to deposit predicted miRNA-target information by using different algorithms, but these databases usually contains lots of false positives. Besides, the validated databases provides only a few miRNA-target information compared to the predicted databases. To reduce incorrect records and increase the number of reliable records, many other databases integrate these predicted miRNA-target information from the databases mentioned above. However, the expression of the same miRNAs in different tissues are different, the realistic regulatory mechanisms could not be figured out in these databases. Moreover, they cannot return the common targets with multiple input miRNAs. To solve these two problems, we construct a database called CSmiRTar (Condition-Specific miRNA Targets). CSmiRTar collects computationally predicted targets of 2588 miRNAs in Human (or 1945 miRNAs in Mouse) from four existing databases (microRNA.org, TargetScan, DIANA-microT and miRDB), and it provides some biological filters which enabling users to search miRNA targets which are expressed only in a specific tissue or related to a specific disease. Moreover, CSmiRTar allows users to search the common targets of multiple miRNAs under a specific biological condition. We believe that CSmiRTar could be helpful for biologists whom want to study the regulatory mechanisms of miRNAs.
The CSmiRTar database is available at http://cosbi.ee.ncku.edu.tw /CSmiRTar/.
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