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BP Neural Network Could Help Improve Pre-miRNA Identification in Various Species
Joint Authors
Zou, Quan
Xuan, Ping
Jiang, Limin
Zhang, Jingjun
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-08-22
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
MicroRNAs (miRNAs) are a set of short (21–24 nt) noncoding RNAs that play significant regulatory roles in cells.
In the past few years, research on miRNA-related problems has become a hot field of bioinformatics because of miRNAs’ essential biological function.
miRNA-related bioinformatics analysis is beneficial in several aspects, including the functions of miRNAs and other genes, the regulatory network between miRNAs and their target mRNAs, and even biological evolution.
Distinguishing miRNA precursors from other hairpin-like sequences is important and is an essential procedure in detecting novel microRNAs.
In this study, we employed backpropagation (BP) neural network together with 98-dimensional novel features for microRNA precursor identification.
Results show that the precision and recall of our method are 95.53% and 96.67%, respectively.
Results further demonstrate that the total prediction accuracy of our method is nearly 13.17% greater than the state-of-the-art microRNA precursor prediction software tools.
American Psychological Association (APA)
Jiang, Limin& Zhang, Jingjun& Xuan, Ping& Zou, Quan. 2016. BP Neural Network Could Help Improve Pre-miRNA Identification in Various Species. BioMed Research International،Vol. 2016, no. 2016, pp.1-11.
https://search.emarefa.net/detail/BIM-1099322
Modern Language Association (MLA)
Jiang, Limin…[et al.]. BP Neural Network Could Help Improve Pre-miRNA Identification in Various Species. BioMed Research International No. 2016 (2016), pp.1-11.
https://search.emarefa.net/detail/BIM-1099322
American Medical Association (AMA)
Jiang, Limin& Zhang, Jingjun& Xuan, Ping& Zou, Quan. BP Neural Network Could Help Improve Pre-miRNA Identification in Various Species. BioMed Research International. 2016. Vol. 2016, no. 2016, pp.1-11.
https://search.emarefa.net/detail/BIM-1099322
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1099322