Low-power architectures for miRNA-target genome wide analysis

In molecular biology, the interaction mechanisms between microRNAs (miRNAs) with their messenger RNA targets are poorly understood. This is the reason why many miRNAtarget prediction methods are available, but their results are often inconsistent. A lot of efforts focus on the quality of the sequence match between miRNA and target rather than on the role of the mRNA secondary structure in which the target is embedded. Nonetheless, it is known that the miRNA secondary structures contribute to target recognition, because there is an energetic cost to freeing base-pairing interactions within mRNA to make the target accessible for miRNA binding. This approach is implemented by PITA (Probability of Interaction by Target Accessibility), a very computational-intensive tool that is able to provide accurate results even when little is know about the conservation of the miRNA. In this paper we propose a new implementation of PITA, called lPITA, able to exploit a coarsegrained parallelism over low power architectures to reduce both execution times and the power consumption.