ArticlePloS one2016
qiRNApredictor: A Novel Computational Program for the Prediction of qiRNAs in Neurospora crassa.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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7 authors at 1 institution in 1 country.
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Abstract
Recently, a new type of small interfering RNAs (qiRNAs) of typically 20~21 nucleotides was found in Neurospora crassa and rice and has been shown to regulate gene silencing in the DNA damage response. Identification of qiRNAs is fundamental for dissecting regulatory functions and molecular mechanisms. In contrast to other expensive and time-consuming experimental methods, the computational prediction of qiRNAs is a conveniently rapid method for gaining valuable information for a subsequent experimental verification. However, no tool existed to date for the prediction of qiRNAs. To this purpose, we developed the novel qiRNA prediction software package qiRNApredictor. This software demonstrates a promising sensitivity of 93.55% and a specificity of 71.61% from the leave-one-out validation. These studies might be beneficial for further experimental investigation. Furthermore, the local package of qiRNApredictor was implemented and made freely available to the academic community at Supplementary material.
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