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qiRNApredictor: A Novel Computational Program for the Prediction of qiRNAs in Neurospora crassa
Author(s) -
Haiyou Deng,
Quan Liu,
Wei Cao,
Rong Gui,
Chengzhang Ma,
Ming Yi,
Yuangen Yao
Publication year - 2016
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0159487
Subject(s) - neurospora crassa , crassa , computational biology , neurospora , computer science , software , identification (biology) , biology , sensitivity (control systems) , bioinformatics , data mining , genetics , gene , engineering , programming language , ecology , electronic engineering , mutant
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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