The microRNA identification step is a part of a plant analytic pipeline. Researches on microRNA identification have been focused extensively on precision, recall, f-measure, and accuracy of computational techniques. However, as the database becomes larger, these computational techniques cannot reduce time complexity to handle the growth. As a result, the identification step becomes a bottleneck in the pipeline. To reduce the response time of the identification step, we proposed a new technique that can discover predictive results faster than the traditional technique. Our technique is based on reordering sequences. The sequences that have higher potential score values will be executed with higher priority. The proposed technique can accelerate the study of plant miRNAs and also can be applied to other computational techniques as well.
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| http://dx.doi.org/10.1016/j.compbiolchem.2018.12.019 | DOI Listing |
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