Paper Info
Title
SgRNA-RF: Identification of SgRNA On-Target Activity With Imbalanced Datasets
Abstract
Single-guide RNA is a guide RNA (gRNA), which guides the insertion or deletion of uridine residues into kinetoplastid during RNA editing. It is a small non-coding RNA that can be combined with pre -mRNA pairing. SgRNA is a critical component of the CRISPR/Cas9 gene knockout system and play an important role in gene editing and gene regulation. It is important to accurately and quickly identify highly on-target activity sgRNAs. Due to its importance, several computational predictors have been proposed to predict sgRNAs on-target activity. All these methods have clearly contributed to the development of this very important field. However, they also have certain limitations. In the paper, we developed a new classifier SgRNA-RF, which extracts the features of nucleic acid composition and structure of on-target activity sgRNA sequence and identified by random forest algorithm. In addition to solving an imbalanced dataset, this paper proposed a new method called CS-Smote. We compared sgRNA-RF with state-of-the-art predictors on the five datasets, and found SgRNA-RF significantly improved the identification accuracy, with accuracies of 0.8636,0.9161,0.894,0.938,0.965,0.77,0.979,0.973, respectively. The user-friendly web server that implements sgRNA-RF is freely available at <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">http://server.malab.cn/sgRNA-RF/</uri> .
Year
DOI
Venue
2022
10.1109/TCBB.2021.3079116
IEEE/ACM Transactions on Computational Biology and Bioinformatics
Keywords
DocType
Volume
Algorithms,CRISPR-Cas Systems,Gene Editing,RNA, Guide
Journal
19
Issue
ISSN
Citations 
4
1545-5963
0
PageRank 
References 
Authors
0.34
13
2
Name
Order
Citations
PageRank
Mengting Niu111.70
quan zou255867.61