AIMC Topic: Proteins

Clear Filters Showing 971 to 980 of 1970 articles

OPUS-Rota3: Improving Protein Side-Chain Modeling by Deep Neural Networks and Ensemble Methods.

Journal of chemical information and modeling Nov 19, 2020
Side-chain modeling is critical for protein structure prediction since the uniqueness of the protein structure is largely determined by its side-chain packing conformation. In this paper, differing from most approaches that rely on rotamer library sa...
Neural Networks, Computer Software Proteins Protein Conformation Gene Library
View on PubMed DOI

Inferring Protein Sequence-Function Relationships with Large-Scale Positive-Unlabeled Learning.

Cell systems Nov 18, 2020
Machine learning can infer how protein sequence maps to function without requiring a detailed understanding of the underlying physical or biological mechanisms. It is challenging to apply existing supervised learning frameworks to large-scale experim...
Proteins Amino Acid Sequence Machine Learning
View on PubMed DOI

DeepFrag-k: a fragment-based deep learning approach for protein fold recognition.

BMC bioinformatics Nov 18, 2020
BACKGROUND: One of the most essential problems in structural bioinformatics is protein fold recognition. In this paper, we design a novel deep learning architecture, so-called DeepFrag-k, which identifies fold discriminative features at fragment leve...
Proteins Protein Folding Deep Learning Computational Biology Neural Networks, Computer
View on PubMed DOI

GODoc: high-throughput protein function prediction using novel k-nearest-neighbor and voting algorithms.

BMC bioinformatics Nov 18, 2020
BACKGROUND: Biological data has grown explosively with the advance of next-generation sequencing. However, annotating protein function with wet lab experiments is time-consuming. Fortunately, computational function prediction can help wet labs formul...
Gene Ontology Politics Proteins Drosophila melanogaster Animals Computational Biology Algorithms
View on PubMed DOI

AK-Score: Accurate Protein-Ligand Binding Affinity Prediction Using an Ensemble of 3D-Convolutional Neural Networks.

International journal of molecular sciences Nov 10, 2020
Accurate prediction of the binding affinity of a protein-ligand complex is essential for efficient and successful rational drug design. Therefore, many binding affinity prediction methods have been developed. In recent years, since deep learning tech...
Deep Learning User-Computer Interface Drug Design Drug Discovery Databases, Protein Molecular Dynamics Simulation Ligands Protein Binding Proteins Humans Neural Networks, Computer Molecular Docking Simulation Computer-Aided Design
View on PubMed DOI

DeepCryoPicker: fully automated deep neural network for single protein particle picking in cryo-EM.

BMC bioinformatics Nov 9, 2020
BACKGROUND: Cryo-electron microscopy (Cryo-EM) is widely used in the determination of the three-dimensional (3D) structures of macromolecules. Particle picking from 2D micrographs remains a challenging early step in the Cryo-EM pipeline due to the di...
Cryoelectron Microscopy Proteins Automation Deep Learning Cluster Analysis
View on PubMed DOI

ReFold-MAP: Protein remote homology detection and fold recognition based on features extracted from profiles.

Analytical biochemistry Nov 6, 2020
Protein remote homology detection and protein fold recognition are two important tasks in protein structure and function prediction. There are three kinds of methods in this field, including the discriminative methods, the alignment methods, and the ...
Sequence Analysis, Protein Protein Folding Sequence Alignment Artificial Intelligence Proteins Databases, Protein
View on PubMed DOI

Matrix Factorization-based Technique for Drug Repurposing Predictions.

IEEE journal of biomedical and health informatics Nov 4, 2020
Classical drug design methodologies are hugely costly and time-consuming, with approximately 85% of the new proposed molecules failing in the first three phases of the FDA drug approval process. Thus, strategies to find alternative indications for al...
Humans Protein Interaction Maps Machine Learning Proteins Algorithms Drug Repositioning
View on PubMed DOI

Protein molecular defect detection method based on a neural network algorithm.

Cellular and molecular biology (Noisy-le-Grand, France) Oct 31, 2020
Proteins, as the largest macromolecules in the body, are among the most important components of the body and play very vital and important roles. These substances are made up of a series of amino acid chains that, depending on the type of protein, th...
Databases, Protein Computational Biology Amino Acid Sequence Protein Structure, Secondary Neural Networks, Computer Proteins Algorithms
View on PubMed

A Machine Learning Protocol for Predicting Protein Infrared Spectra.

Journal of the American Chemical Society Oct 30, 2020
Infrared (IR) absorption provides important chemical fingerprints of biomolecules. Protein secondary structure determination from IR spectra is tedious since its theoretical interpretation requires repeated expensive quantum-mechanical calculations i...
Protein Folding Proteins Amides Temperature Peptides Spectrophotometry, Infrared Protein Structure, Secondary Quantum Theory Ubiquitin Machine Learning
View on PubMed DOI
Popular Topics
Recent Journals