Protein Secondary Structure Prediction Using Cascaded Feature Learning Model-Reference-Cited by-同舟云学术

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Protein Secondary Structure Prediction Using Cascaded Feature Learning Model

Published:2023-06 Issue: Volume:140 Page:110242
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

S. Geethu,E.R. Vimina^ORCID

Publisher

Elsevier BV

Subject

Software

Reference53 articles.

1. Protein folding by zipping and assembly;Ozkan;Proc. Natl. Acad. Sci. USA,2007

2. Three-dimensional protein structure prediction–exploratory review;Geethu,2021

3. Protein secondary structure prediction: A survey of state of the art;Jiang;J. Mol. Graph.,2017

4. Deep learning in drug discovery;Gawehn.;Mol. Inform.,2016

5. RaptorX-Property: a web server for protein structure property prediction;Wang;Nucleic Acids Res.,2016

Cited by 4 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. SERT-StructNet: Protein secondary structure prediction method based on multi-factor hybrid deep model;Computational and Structural Biotechnology Journal;2024-12

2. Machine learning for predicting protein properties: A comprehensive review;Neurocomputing;2024-09

3. Self-attention and asymmetric multi-layer perceptron-gated recurrent unit blocks for protein secondary structure prediction;Applied Soft Computing;2024-07

4. A Hybrid Bidirectional Long Short-Term Memory and Bidirectional Gated Recurrent Unit Architecture for Protein Secondary Structure Prediction;IEEE Access;2024

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