AIMC Topic: Sequence Analysis, Protein

Clear Filters Showing 31 to 40 of 262 articles

DeepRHD: An efficient hybrid feature extraction technique for protein remote homology detection using deep learning strategies.

Computational biology and chemistry Aug 3, 2022
In computational biology, the Protein Remote homology Detection technique (PRHD) has got undeniable significance. It is mostly important for structure and function identification of a protein sequence. The previous years have seen a challenge that la...
Amino Acid Sequence Sequence Homology, Amino Acid Sequence Analysis, Protein Deep Learning Proteins Algorithms
View on PubMed DOI

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

Journal of molecular biology Apr 22, 2022
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 ...
Intrinsically Disordered Proteins Protein Structure, Secondary Sequence Analysis, Protein Computational Biology Amino Acid Sequence Neural Networks, Computer Software
View on PubMed DOI

Positional SHAP (PoSHAP) for Interpretation of machine learning models trained from biological sequences.

PLoS computational biology Jan 28, 2022
Machine learning with multi-layered artificial neural networks, also known as "deep learning," is effective for making biological predictions. However, model interpretation is challenging, especially for sequential input data used with recurrent neur...
Models, Biological Amino Acid Sequence Sequence Analysis, Protein Macaca mulatta Binding Sites Peptides Deep Learning Computational Biology Humans Animals
View on PubMed DOI

ProALIGN: Directly Learning Alignments for Protein Structure Prediction via Exploiting Context-Specific Alignment Motifs.

Journal of computational biology : a journal of computational molecular cell biology Jan 21, 2022
Template-based modeling (TBM), including homology modeling and protein threading, is one of the most reliable techniques for protein structure prediction. It predicts protein structure by building an alignment between the query sequence under predict...
Algorithms Deep Learning Computational Biology Neural Networks, Computer Software Protein Conformation Sequence Alignment Amino Acid Motifs Models, Molecular Amino Acid Sequence Proteins Sequence Analysis, Protein
View on PubMed DOI

Enhancing protein inter-residue real distance prediction by scrutinising deep learning models.

Scientific reports Jan 17, 2022
Protein structure prediction (PSP) has achieved significant progress lately via prediction of inter-residue distances using deep learning models and exploitation of the predictions during conformational search. In this context, prediction of large in...
Amino Acid Sequence Deep Learning Neural Networks, Computer Datasets as Topic Sequence Analysis, Protein Proteins Models, Molecular
View on PubMed DOI

Protein embeddings and deep learning predict binding residues for various ligand classes.

Scientific reports Dec 13, 2021
One important aspect of protein function is the binding of proteins to ligands, including small molecules, metal ions, and macromolecules such as DNA or RNA. Despite decades of experimental progress many binding sites remain obscure. Here, we propose...
Molecular Docking Simulation Software Deep Learning Protein Binding Binding Sites Protein Conformation Metals Ligands Sequence Analysis, Protein Nucleic Acids
View on PubMed DOI

Protein Fold Recognition From Sequences Using Convolutional and Recurrent Neural Networks.

IEEE/ACM transactions on computational biology and bioinformatics Dec 8, 2021
The identification of a protein fold type from its amino acid sequence provides important insights about the protein 3D structure. In this paper, we propose a deep learning architecture that can process protein residue-level features to address the p...
Sequence Analysis, Protein Computational Biology Algorithms Proteins Deep Learning Protein Folding
View on PubMed DOI

Protein Fold Recognition Based on Auto-Weighted Multi-View Graph Embedding Learning Model.

IEEE/ACM transactions on computational biology and bioinformatics Dec 8, 2021
Protein fold recognition is critical for studies of the protein structure prediction and drug design. Several methods have been proposed to obtain discriminative features from the protein sequences for fold recognition. However, the ensemble methods ...
Protein Folding Sequence Alignment Sequence Analysis, Protein Machine Learning Databases, Protein Computational Biology Amino Acid Sequence Algorithms Proteins
View on PubMed DOI

Improved Predicting of The Sequence Specificities of RNA Binding Proteins by Deep Learning.

IEEE/ACM transactions on computational biology and bioinformatics Dec 8, 2021
RNA-binding proteins (RBPs) have a significant role in various regulatory tasks. However, the mechanism by which RBPs identify the subsequence target RNAs is still not clear. In recent years, several machine and deep learning-based computational mode...
Sequence Analysis, Protein Conserved Sequence Amino Acid Motifs Deep Learning Computational Biology Humans RNA-Binding Proteins Animals
View on PubMed DOI

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...
Support Vector Machine Proteins Amino Acid Sequence Protein Structure, Secondary Databases, Protein Machine Learning Computational Biology Sequence Analysis, Protein
View on PubMed DOI
Popular Topics
Recent Journals