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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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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Secondary structure specific simpler prediction models for protein backbone angles [PDF]
BMC Bioinformatics, 2022 Motivation Protein backbone angle prediction has achieved significant accuracy improvement with the development of deep learning methods. Usually the same deep learning model is used in making prediction for all residues regardless of the categories of ...
M. A. Hakim Newton +3 more
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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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Deep Ensemble Learning with Atrous Spatial Pyramid Networks for Protein Secondary Structure Prediction [PDF]
Biomolecules, 2022 The secondary structure of proteins is significant for studying the three-dimensional structure and functions of proteins. Several models from image understanding and natural language modeling have been successfully adapted in the protein sequence study ...
Yuzhi Guo +4 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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Impact of Multi-Factor Features on Protein Secondary Structure Prediction [PDF]
BiomoleculesProtein secondary structure prediction (PSSP) plays a crucial role in resolving protein functions and properties. Significant progress has been made in this field in recent years, and the use of a variety of protein-related features, including amino acid
Benzhi Dong +5 more
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A secondary structure-based position-specific scoring matrix applied to the improvement in protein secondary structure prediction. [PDF]
PLoS ONE, 2021 Protein secondary structure prediction (SSP) has a variety of applications; however, there has been relatively limited improvement in accuracy for years.
Teng-Ruei Chen +4 more
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The Future of Protein Secondary Structure Prediction Was Invented by Oleg Ptitsyn [PDF]
Biomolecules, 2020 When Oleg Ptitsyn and his group published the first secondary structure prediction for a protein sequence, they started a research field that is still active today.
Daniel Rademaker +5 more
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