Using the Chou’s 5-steps rule to predict splice junctions with interpretable bidirectional long short-term memory networks-Reference-Cited by-同舟云学术

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Using the Chou’s 5-steps rule to predict splice junctions with interpretable bidirectional long short-term memory networks

Published:2020-01 Issue: Volume:116 Page:103558
ISSN:0010-4825
Container-title:Computers in Biology and Medicine
language:en
Short-container-title:Computers in Biology and Medicine

Author:

Dutta Aparajita,Dalmia Aman,R Athul,Singh Kusum Kumari,Anand Ashish

Funder

SERB, India

MHRD, Govt of India

Department of Biotechnology, Govt. of India

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications

Reference77 articles.

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2. Deeptarget: end-to-end learning framework for microRNA target prediction using deep recurrent neural networks;Lee,2016

3. DeepCpG: accurate prediction of single-cell DNA methylation states using deep learning;Angermueller;Genome Biol.,2017

4. Fast model-based protein homology detection without alignment;Hochreiter;Bioinformatics,2007

5. Continuous distributed representation of biological sequences for deep proteomics and genomics;Asgari;PLoS One,2015

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2. SpliceCannon: A novel framework for the prediction of canonical and non-canonical splice sites based on deep learning;2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM);2023-12-05

3. An Effective Deep Learning-Based Architecture for Prediction of N7-Methylguanosine Sites in Health Systems;Electronics;2022-06-20

4. Deep learning models for identification of splice junctions across species;2021-06-14

5. SpliceViNCI: Visualizing the splicing of non-canonical introns through recurrent neural networks;2020-02-10

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