Abstract
Micro RNAs (miRNAs) are small RNA molecules that target protein coding genes and inhibit protein production. Since experimental identification of miRNA targets poses difficulties, computational miRNA target prediction is one of the key means in deciphering the role of microRNAs in development and disease. However, these computational methods are CPU-intensive. For example, the predictions for a single miRNA molecule on the whole human genome according to a popular target prediction method require about 30 minutes. Such performance is a hindrance to the biologists’ requirement for near-real time target prediction. In this paper, we present TARCLOUD, a Cloud-based target prediction solution built on Microsoft’s Azure platform. TARCLOUD is a highly-scalable solution based on distributed programming models that provides near-real time predictions to its users through an easy and intuitive interface. The work has been selected as one of the pilot use cases for the VENUS-C FP7 Research Infrastructures Program.
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© 2012 Springer-Verlag Berlin Heidelberg
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Vergoulis, T., Alexakis, M., Dalamagas, T., Maragkakis, M., Hatzigeorgiou, A.G., Sellis, T. (2012). TARCLOUD: A Cloud-Based Platform to Support miRNA Target Prediction. In: Ailamaki, A., Bowers, S. (eds) Scientific and Statistical Database Management. SSDBM 2012. Lecture Notes in Computer Science, vol 7338. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31235-9_48
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DOI: https://doi.org/10.1007/978-3-642-31235-9_48
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31234-2
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