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.
Keywords
- Regression analysis
- Relevance Vector Machines
- microarray data analysis
- microRNA regulation
- missing data imputation
- promoter elements
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© 2015 Springer International Publishing Switzerland
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Oğul, H., Tuncer, M.E. (2015). Predicting microRNA Expression from Sequence. In: Lacković, I., Vasic, D. (eds) 6th European Conference of the International Federation for Medical and Biological Engineering. IFMBE Proceedings, vol 45. Springer, Cham. https://doi.org/10.1007/978-3-319-11128-5_150
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DOI: https://doi.org/10.1007/978-3-319-11128-5_150
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11127-8
Online ISBN: 978-3-319-11128-5
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