Deep learning for protein secondary structure prediction: Pre and post-AlphaFold [PDF]
Computational and Structural Biotechnology Journal, 2022 This paper aims to provide a comprehensive review of the trends and challenges of deep neural networks for protein secondary structure prediction (PSSP). In recent years, deep neural networks have become the primary method for protein secondary structure
Dewi Pramudi Ismi +2 more
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Protein Secondary Structure Prediction With a Reductive Deep Learning Method [PDF]
Frontiers in Bioengineering and Biotechnology, 2021 Protein secondary structures have been identified as the links in the physical processes of primary sequences, typically random coils, folding into functional tertiary structures that enable proteins to involve a variety of biological events in life ...
Zhiliang Lyu +5 more
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JPred4: a protein secondary structure prediction server. [PDF]
Nucleic Acids Res, 2015 JPred4 (http://www.compbio.dundee.ac.uk/jpred4) is the latest version of the popular JPred protein secondary structure prediction server which provides predictions by the JNet algorithm, one of the most accurate methods for secondary structure prediction.
Drozdetskiy A +3 more
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OCLSTM: Optimized convolutional and long short-term memory neural network model for protein secondary structure prediction. [PDF]
PLoS ONE, 2021 Protein secondary structure prediction is extremely important for determining the spatial structure and function of proteins. In this paper, we apply an optimized convolutional neural network and long short-term memory neural network models to protein ...
Yawu Zhao, Yihui Liu
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Protein secondary structure prediction with context convolutional neural network. [PDF]
RSC Adv, 2019 Protein secondary structure (SS) prediction is important for studying protein structure and function. Both traditional machine learning methods and deep learning neural networks have been utilized and great progress has been achieved in approaching the ...
Long S, Tian P.
europepmc +4 more sources
Protein secondary structure prediction using a small training set (compact model) combined with a Complex-valued neural network approach. [PDF]
BMC Bioinformatics, 2016 Protein secondary structure prediction (SSP) has been an area of intense research interest. Despite advances in recent methods conducted on large datasets, the estimated upper limit accuracy is yet to be reached.
Rashid S +4 more
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Discovering the Ultimate Limits of Protein Secondary Structure Prediction [PDF]
Biomolecules, 2021 Secondary structure prediction (SSP) of proteins is an important structural biology technique with many applications. There have been ~300 algorithms published in the past seven decades with fierce competition in accuracy.
Chia-Tzu Ho +4 more
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Convolution-Bidirectional Temporal Convolutional Network for Protein Secondary Structure Prediction
IEEE Access, 2022 As a basic feature extraction method, convolutional neural networks have some information loss problems when dealing with sequence problems, and a temporal convolutional network can compensate for this problem.
Yunqing Zhang, Yuming Ma, Yihui Liu
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Ensemble deep learning models for protein secondary structure prediction using bidirectional temporal convolution and bidirectional long short-term memory [PDF]
Frontiers in Bioengineering and Biotechnology, 2023 Protein secondary structure prediction (PSSP) is a challenging task in computational biology. However, existing models with deep architectures are not sufficient and comprehensive for deep long-range feature extraction of long sequences.
Lu Yuan, Yuming Ma, Yihui Liu
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Multistage Combination Classifier Augmented Model for Protein Secondary Structure Prediction [PDF]
Frontiers in Genetics, 2022 In the field of bioinformatics, understanding protein secondary structure is very important for exploring diseases and finding new treatments. Considering that the physical experiment-based protein secondary structure prediction methods are time ...
Xu Zhang +6 more
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