AIMC Topic: Protein Structure, Secondary

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Deep Ensemble Learning with Atrous Spatial Pyramid Networks for Protein Secondary Structure Prediction.

Biomolecules
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 st...

Deep-Learning-Assisted Stratification of Amyloid Beta Mutants Using Drying Droplet Patterns.

Advanced materials (Deerfield Beach, Fla.)
The development of simple and accurate methods to predict mutations in proteins remains an unsolved challenge in modern biochemistry. It is discovered that critical information about primary and secondary peptide structures can be inferred from the s...

Recognition of Protein Network for Bioinformatics Knowledge Analysis Using Support Vector Machine.

BioMed research international
Protein is the material foundation of living things, and it directly takes part in and runs the process of living things itself. Predicting protein complexes helps us understand the structure and function of complexes, and it is an important foundati...

Prediction of Disordered Regions in Proteins with Recurrent Neural Networks and Protein Dynamics.

Journal of molecular biology
The role of intrinsically disordered protein regions (IDRs) in cellular processes has become increasingly evident over the last years. These IDRs continue to challenge structural biology experiments because they lack a well-defined conformation, and ...

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

BMC genomics
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 ...

End-to-End Deep Learning Model to Predict and Design Secondary Structure Content of Structural Proteins.

ACS biomaterials science & engineering
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...

Predicting Local Protein 3D Structures Using Clustering Deep Recurrent Neural Network.

IEEE/ACM transactions on computational biology and bioinformatics
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...

Secondary structure specific simpler prediction models for protein backbone angles.

BMC bioinformatics
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...

Enhanced Protein Structural Class Prediction Using Effective Feature Modeling and Ensemble of Classifiers.

IEEE/ACM transactions on computational biology and bioinformatics
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...

Accurate prediction of protein torsion angles using evolutionary signatures and recurrent neural network.

Scientific reports
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...