AIMC Topic: Protein Structure, Secondary

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ENNGene: an Easy Neural Network model building tool for Genomics.

BMC genomics Mar 31, 2022
BACKGROUND: The recent big data revolution in Genomics, coupled with the emergence of Deep Learning as a set of powerful machine learning methods, has shifted the standard practices of machine learning for Genomics. Even though Deep Learning methods ...
Genomics Neural Networks, Computer Protein Structure, Secondary Machine Learning
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End-to-End Deep Learning Model to Predict and Design Secondary Structure Content of Structural Proteins.

ACS biomaterials science & engineering Feb 7, 2022
Structural proteins are the basis of many biomaterials and key construction and functional components of all life. Further, it is well-known that the diversity of proteins' function relies on their local structures derived from their primary amino ac...
Deep Learning Amino Acid Sequence Proteins Protein Structure, Secondary
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Predicting Local Protein 3D Structures Using Clustering Deep Recurrent Neural Network.

IEEE/ACM transactions on computational biology and bioinformatics Feb 3, 2022
Since protein 3D structure prediction is very important for biochemical study and drug design, researchers have developed many machine learning algorithms to predict protein 3D structures using the sequence information only. Understanding the sequenc...
Algorithms Cluster Analysis Proteins Protein Structure, Secondary Neural Networks, Computer Machine Learning
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Secondary structure specific simpler prediction models for protein backbone angles.

BMC bioinformatics Jan 4, 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...
Neural Networks, Computer Machine Learning Proteins Protein Structure, Secondary
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Enhanced Protein Structural Class Prediction Using Effective Feature Modeling and Ensemble of Classifiers.

IEEE/ACM transactions on computational biology and bioinformatics Dec 8, 2021
Protein Secondary Structural Class (PSSC) information is important in investigating further challenges of protein sequences like protein fold recognition, protein tertiary structure prediction, and analysis of protein functions for drug discovery. Id...
Databases, Protein Amino Acid Sequence Support Vector Machine Proteins Protein Structure, Secondary Sequence Analysis, Protein Machine Learning Computational Biology
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Accurate prediction of protein torsion angles using evolutionary signatures and recurrent neural network.

Scientific reports Oct 26, 2021
The amino acid sequence of a protein contains all the necessary information to specify its shape, which dictates its biological activities. However, it is challenging and expensive to experimentally determine the three-dimensional structure of protei...
Predictive Value of Tests Protein Structure, Secondary Protein Structure, Tertiary Proteins Neural Networks, Computer Databases, Protein Software Evolution, Molecular
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TopProperty: Robust Metaprediction of Transmembrane and Globular Protein Features Using Deep Neural Networks.

Journal of chemical theory and computation Oct 18, 2021
Transmembrane proteins (TMPs) are critical components of cellular life. However, due to experimental challenges, the number of experimentally resolved TMP structures is severely underrepresented in databases compared to their cellular abundance. Pred...
Databases, Protein Protein Structure, Secondary Computational Biology Membrane Proteins Algorithms Neural Networks, Computer
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Mapping the glycosyltransferase fold landscape using interpretable deep learning.

Nature communications Sep 27, 2021
Glycosyltransferases (GTs) play fundamental roles in nearly all cellular processes through the biosynthesis of complex carbohydrates and glycosylation of diverse protein and small molecule substrates. The extensive structural and functional diversifi...
Amino Acid Sequence Datasets as Topic Glycosylation Databases, Genetic Sequence Alignment Protein Structure, Tertiary Protein Structure, Secondary Protein Folding Deep Learning Glycosyltransferases Computational Biology
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Testing machine learning techniques for general application by using protein secondary structure prediction. A brief survey with studies of pitfalls and benefits using a simple progressive learning approach.

Computers in biology and medicine Sep 23, 2021
Many researchers have recently used the prediction of protein secondary structure (local conformational states of amino acid residues) to test advances in predictive and machine learning technology such as Neural Net Deep Learning. Protein secondary ...
Databases, Protein Protein Structure, Secondary Machine Learning Algorithms Proteins
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Research on RNA secondary structure predicting via bidirectional recurrent neural network.

BMC bioinformatics Sep 8, 2021
BACKGROUND: RNA secondary structure prediction is an important research content in the field of biological information. Predicting RNA secondary structure with pseudoknots has been proved to be an NP-hard problem. Traditional machine learning methods...
RNA Nucleic Acid Conformation Protein Structure, Secondary Neural Networks, Computer Algorithms
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