Using miRNA-Analyzer for the Analysis of miRNA Data
AbstractMicroRNAs (miRNAs) are small biological molecules that play an important role during the mechanisms of protein formation. Recent findings have demonstrated that they act as both positive and negative regulators of protein formation. Thus, the investigation of miRNAs, i.e., the determination of their level of expression, has developed a huge interest in the scientific community. One of the leading technologies for extracting miRNA data from biological samples is the miRNA Affymetrix platform. It provides the quantification of the level of expression of the miRNA in a sample, thus enabling the accumulation of data and allowing the determination of relationships among miRNA, genes, and diseases. Unfortunately, there is a lack of a comprehensive platform able to provide all the functions needed for the extraction of information from miRNA data. We here present miRNA-Analyzer, a complete software tool providing primary functionalities for miRNA data analysis. The current version of miRNA-Analyzer wraps the Affymetrix QCTool for the preprocessing of binary data files, and then provides feature selection (the filtering by species and by the associated p-value of preprocessed files). Finally, preprocessed and filtered data are analyzed by the Multiple Experiment Viewer (T-MEV) and Short Time Series Expression Miner (STEM) tools, which are also wrapped into miRNA-Analyzer, thus providing a unique environment for miRNA data analysis. The tool offers a plug-in interface so it is easily extensible by adding other algorithms as plug-ins. Users may download the tool freely for academic use at
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Guzzi, P.H.; Tradigo, G.; Veltri, P. Using miRNA-Analyzer for the Analysis of miRNA Data. Microarrays 2016, 5, 29.
Guzzi PH, Tradigo G, Veltri P. Using miRNA-Analyzer for the Analysis of miRNA Data. Microarrays. 2016; 5(4):29.Chicago/Turabian Style
Guzzi, Pietro H.; Tradigo, Giuseppe; Veltri, Pierangelo. 2016. "Using miRNA-Analyzer for the Analysis of miRNA Data." Microarrays 5, no. 4: 29.
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