CRIECNN: Ensemble convolutional neural network and advanced feature extraction methods for the precise forecasting of circRNA-RBP binding sites-Reference-Cited by-同舟云学术

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CRIECNN: Ensemble convolutional neural network and advanced feature extraction methods for the precise forecasting of circRNA-RBP binding sites

Published:2024-05 Issue: Volume:174 Page:108466
ISSN:0010-4825
Container-title:Computers in Biology and Medicine
language:en
Short-container-title:Computers in Biology and Medicine

Author:

Lasantha Dilan^ORCID,Vidanagamachchi Sugandima,Nallaperuma Sam

Publisher

Elsevier BV

Reference53 articles.

1. Structure, regulation, and function of linear and circular long non-coding RNAs;Qin;Front. Genet.,2020

2. Extensive translation of circular RNAs driven by N6-methyladenosine;Yang;Cell Res.,2017

3. Deep learning and ensemble deep learning for circRNA-RBP interaction prediction in the last decade: A review;Lasantha;Eng. Appl. Artif. Intell.,2023

4. Circular RNAs: regulatory molecules with great promise;Conn;EMBO J.,2018

5. A ceRNA hypothesis: the Rosetta stone of a hidden RNA language?;Salmena;Cell,2011

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Two heads are better than one: Unravelling the potential Impact of Artificial Intelligence in nanotechnology;Nano TransMed;2024-12

2. MSTCRB: Predicting circRNA-RBP interaction by extracting multi-scale features based on transformer and attention mechanism;International Journal of Biological Macromolecules;2024-10

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