AIMC Topic: Protein Structure, Secondary

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Variable Length Character N-Gram Embedding of Protein Sequences for Secondary Structure Prediction.

Protein and peptide letters Jan 1, 2021
BACKGROUND: The prediction of a protein's secondary structure from its amino acid sequence is an essential step towards predicting its 3-D structure. The prediction performance improves by incorporating homologous multiple sequence alignment informat...
Deep Learning Proteins Databases, Protein Protein Structure, Secondary Sequence Analysis, Protein
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OPUS-TASS: a protein backbone torsion angles and secondary structure predictor based on ensemble neural networks.

Bioinformatics (Oxford, England) Dec 22, 2020
MOTIVATION: Predictions of protein backbone torsion angles (ϕ and ψ) and secondary structure from sequence are crucial subproblems in protein structure prediction. With the development of deep learning approaches, their accuracies have been significa...
Neural Networks, Computer Proteins Protein Structure, Secondary
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SAINT: self-attention augmented inception-inside-inception network improves protein secondary structure prediction.

Bioinformatics (Oxford, England) Nov 1, 2020
MOTIVATION: Protein structures provide basic insight into how they can interact with other proteins, their functions and biological roles in an organism. Experimental methods (e.g. X-ray crystallography and nuclear magnetic resonance spectroscopy) fo...
Neural Networks, Computer Deep Learning Proteins Databases, Protein Protein Structure, Secondary
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Graph neural representational learning of RNA secondary structures for predicting RNA-protein interactions.

Bioinformatics (Oxford, England) Jul 1, 2020
MOTIVATION: RNA-protein interactions are key effectors of post-transcriptional regulation. Significant experimental and bioinformatics efforts have been expended on characterizing protein binding mechanisms on the molecular level, and on highlighting...
Neural Networks, Computer Software Protein Binding RNA Protein Structure, Secondary
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Brewery: deep learning and deeper profiles for the prediction of 1D protein structure annotations.

Bioinformatics (Oxford, England) Jun 1, 2020
MOTIVATION: Protein structural annotations (PSAs) are essential abstractions to deal with the prediction of protein structures. Many increasingly sophisticated PSAs have been devised in the last few decades. However, the need for annotations that are...
Deep Learning Computational Biology Proteins Solvents Protein Structure, Secondary
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Redundancy-weighting the PDB for detailed secondary structure prediction using deep-learning models.

Bioinformatics (Oxford, England) Jun 1, 2020
MOTIVATION: The Protein Data Bank (PDB), the ultimate source for data in structural biology, is inherently imbalanced. To alleviate biases, virtually all structural biology studies use nonredundant (NR) subsets of the PDB, which include only a fracti...
Machine Learning Deep Learning Computational Biology Databases, Protein Protein Structure, Secondary
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MUFold-SSW: a new web server for predicting protein secondary structures, torsion angles and turns.

Bioinformatics (Oxford, England) Feb 15, 2020
MOTIVATION: Protein secondary structure and backbone torsion angle prediction can provide important information for predicting protein 3D structures and protein functions. Our new methods MUFold-SS, MUFold-Angle, MUFold-BetaTurn and MUFold-GammaTurn,...
Neural Networks, Computer Computers Proteins Amino Acid Sequence Protein Structure, Secondary
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Prediction of mRNA subcellular localization using deep recurrent neural networks.

Bioinformatics (Oxford, England) Jul 15, 2019
MOTIVATION: Messenger RNA subcellular localization mechanisms play a crucial role in post-transcriptional gene regulation. This trafficking is mediated by trans-acting RNA-binding proteins interacting with cis-regulatory elements called zipcodes. Whi...
Neural Networks, Computer Deep Learning RNA, Messenger Protein Structure, Secondary
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Improving prediction of protein secondary structure, backbone angles, solvent accessibility and contact numbers by using predicted contact maps and an ensemble of recurrent and residual convolutional neural networks.

Bioinformatics (Oxford, England) Jul 15, 2019
MOTIVATION: Sequence-based prediction of one dimensional structural properties of proteins has been a long-standing subproblem of protein structure prediction. Recently, prediction accuracy has been significantly improved due to the rapid expansion o...
Neural Networks, Computer Computational Biology Proteins Amino Acid Sequence Solvents Protein Structure, Secondary
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ConDo: protein domain boundary prediction using coevolutionary information.

Bioinformatics (Oxford, England) Jul 15, 2019
MOTIVATION: Domain boundary prediction is one of the most important problems in the study of protein structure and function. Many sequence-based domain boundary prediction methods are either template-based or machine learning (ML) based. ML-based met...
Machine Learning Proteins Protein Domains Protein Structure, Secondary Sequence Alignment
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