Predicting microRNA Expression from Sequence

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2015

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Abstract

Given the promoter sequence of a microRNA, we attempt to predict its expression using a regression model learnt from the expression levels of other microRNAs obtained through a microarray experiment. To our knowledge, this is the first study that evaluates the predictability of microRNA expression from sequence. The promising results encourage the use of the system as a supporting means for microarray missing data imputation or completing old experiments with new explorations.

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Regression analysis, Relevance Vector Machines, microarray data analysis, microRNA regulation. missing data imputation, promoter elements

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