Prediction of N6-methyladenosine sites using convolution neural network model based on distributed feature representations
Author:
Funder
National Research Foundation (NRF), Korea
Korean government
Publisher
Elsevier BV
Subject
Artificial Intelligence,Cognitive Neuroscience
Reference68 articles.
1. Intelligent computational model for classification of sub-Golgi protein using oversampling and fisher feature selection methods;Ahmad;Artificial Intelligence in Medicine,2017
2. IMethyl-STTNC: Identification of N6-methyladenosine sites by extending the idea of SAAC into Chou’s PseAAC to formulate RNA sequences;Akbar;Journal of Theoretical Biology,2018
3. IRNA-PseTNC: identification of RNA 5-methylcytosine sites using hybrid vector space of pseudo nucleotide composition;Akbar;Frontiers of Computer Science,2020
4. Predicting the sequence specificities of DNA-and RNA-binding proteins by deep learning;Alipanahi;Nature biotechnology,2015
5. The RNA modification database, RNAMDB: 2011 update;Cantara;Nucleic Acids Research,2011
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