FN Clarivate Analytics Web of Science
VR 1.0
PT J
AN 30425123
DT Journal Article
TI Gene2vec: gene subsequence embedding for prediction of mammalian N6-methyladenosine sites from mRNA.
AU Zou, Quan
   Xing, Pengwei
   Wei, Leyi
   Liu, Bin
SO RNA (New York, N.Y.)
VL 25
IS 2
PS 205-218
PY 2019
PD 2019 Feb (Epub 2018 Nov 13)
LA English
U1 1
U2 1
AB N 6-Methyladenosine (m6A) refers to methylation modification of the adenosine nucleotide acid at the nitrogen-6 position. Many conventional computational methods for identifying N 6-methyladenosine sites are limited by the small amount of data available. Taking advantage of the thousands of m6A sites detected by high-throughput sequencing, it is now possible to discover the characteristics of m6A sequences using deep learning techniques. To the best of our knowledge, our work is the first attempt to use word embedding and deep neural networks for m6A prediction from mRNA sequences. Using four deep neural networks, we developed a model inferred from a larger sequence shifting window that can predict m6A accurately and robustly. Four prediction schemes were built with various RNA sequence representations and optimized convolutional neural networks. The soft voting results from the four deep networks were shown to outperform all of the state-of-the-art methods. We evaluated these predictors mentioned above on a rigorous independent test data set and proved that our proposed method outperforms the state-of-the-art predictors. The training, independent, and cross-species testing data sets are much larger than in previous studies, which could help to avoid the problem of overfitting. Furthermore, an online prediction web server implementing the four proposed predictors has been built and is available at http://server.malab.cn/Gene2vec/. © 2019 Zou et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.
C1 Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, 610051 Chengdu, China.; School of Computer Science and Technology, Tianjin University, 300350 Tianjin, China.; School of Computer Science and Technology, Harbin Institute of Technology, 150001 Shenzhen, China.
ID N6-methyladenosine; RNA word embedding; deep learning; mRNA; machine learning
SN 1469-9001
JC 9509184
PA United States
SA In-Data-Review
RC  / 17 Jan 2019
PE 13 Nov 2018
DI 10.1261/rna.069112.118
UT MEDLINE:30425123
DA 2019-01-24
ER

EF