Utilizing Selected Di- and Trinucleotides of siRNA to Predict RNAi Activity
Joint Authors
Han, Ye
Liu, Yuanning
Zhang, Hao
He, Fei
Shu, Chonghe
Dong, Liyan
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-01-24
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Small interfering RNAs (siRNAs) induce posttranscriptional gene silencing in various organisms.
siRNAs targeted to different positions of the same gene show different effectiveness; hence, predicting siRNA activity is a crucial step.
In this paper, we developed and evaluated a powerful tool named “siRNApred” with a new mixed feature set to predict siRNA activity.
To improve the prediction accuracy, we proposed 2-3NTs as our new features.
A Random Forest siRNA activity prediction model was constructed using the feature set selected by our proposed Binary Search Feature Selection (BSFS) algorithm.
Experimental data demonstrated that the binding site of the Argonaute protein correlates with siRNA activity.
“siRNApred” is effective for selecting active siRNAs, and the prediction results demonstrate that our method can outperform other current siRNA activity prediction methods in terms of prediction accuracy.
American Psychological Association (APA)
Han, Ye& Liu, Yuanning& Zhang, Hao& He, Fei& Shu, Chonghe& Dong, Liyan. 2017. Utilizing Selected Di- and Trinucleotides of siRNA to Predict RNAi Activity. Computational and Mathematical Methods in Medicine،Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1142161
Modern Language Association (MLA)
Han, Ye…[et al.]. Utilizing Selected Di- and Trinucleotides of siRNA to Predict RNAi Activity. Computational and Mathematical Methods in Medicine No. 2017 (2017), pp.1-12.
https://search.emarefa.net/detail/BIM-1142161
American Medical Association (AMA)
Han, Ye& Liu, Yuanning& Zhang, Hao& He, Fei& Shu, Chonghe& Dong, Liyan. Utilizing Selected Di- and Trinucleotides of siRNA to Predict RNAi Activity. Computational and Mathematical Methods in Medicine. 2017. Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1142161
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1142161