DNSS2: Improved ab initio protein secondary structure prediction using advanced deep learning architectures. [PDF]
Proteins, 2021 Motivation Accurate prediction of protein secondary structure (alpha-helix, beta-strand and coil) is a crucial step for protein inter-residue contact prediction and ab initio tertiary structure prediction.
Guo Z, Hou J, Cheng J.
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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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Improved Chou-Fasman method for protein secondary structure prediction [PDF]
BMC Bioinformatics, 2006 Background Protein secondary structure prediction is a fundamental and important component in the analytical study of protein structure and functions. The prediction technique has been developed for several decades.
Huang Zhengge, Gu Fei, Chen Hang
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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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BeStSel: a web server for accurate protein secondary structure prediction and fold recognition from the circular dichroism spectra. [PDF]
Nucleic Acids Res, 2018 Circular dichroism (CD) spectroscopy is a widely used method to study the protein secondary structure. However, for decades, the general opinion was that the correct estimation of β-sheet content is challenging because of the large spectral and ...
Micsonai A +8 more
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Sixty-five years of the long march in protein secondary structure prediction: the final stretch? [PDF]
Brief Bioinform, 2018 Protein secondary structure prediction began in 1951 when Pauling and Corey predicted helical and sheet conformations for protein polypeptide backbone even before the first protein structure was determined.
Yang Y +6 more
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Protein Secondary Structure Prediction Using Deep Convolutional Neural Fields. [PDF]
Sci Rep, 2016 Protein secondary structure (SS) prediction is important for studying protein structure and function. When only the sequence (profile) information is used as input feature, currently the best predictors can obtain ~80% Q3 accuracy, which has not been ...
Wang S, Peng J, Ma J, Xu J.
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Combining Deep Neural Networks for Protein Secondary Structure Prediction
IEEE Access, 2020 By combining convolutional neural networks (CNN) and long short term memory networks (LSTM) into the learning structure, this paper presents a supervised learning method called combining deep neural networks (CDNN) for protein secondary structure ...
Shusen Zhou +4 more
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Deeper Profiles and Cascaded Recurrent and Convolutional Neural Networks for state-of-the-art Protein Secondary Structure Prediction. [PDF]
Sci Rep, 2019 Protein Secondary Structure prediction has been a central topic of research in Bioinformatics for decades. In spite of this, even the most sophisticated ab initio SS predictors are not able to reach the theoretical limit of three-state prediction ...
Torrisi M, Kaleel M, Pollastri G.
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DeepACLSTM: deep asymmetric convolutional long short-term memory neural models for protein secondary structure prediction. [PDF]
BMC Bioinformatics, 2019 Protein secondary structure (PSS) is critical to further predict the tertiary structure, understand protein function and design drugs. However, experimental techniques of PSS are time consuming and expensive, and thus it’s very urgent to develop ...
Guo Y, Li W, Wang B, Liu H, Zhou D.
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