AIMC Topic: Protein Folding

Clear Filters Showing 111 to 120 of 165 articles

Adaptive local learning in sampling based motion planning for protein folding.

BMC systems biology Aug 1, 2016
BACKGROUND: Simulating protein folding motions is an important problem in computational biology. Motion planning algorithms, such as Probabilistic Roadmap Methods, have been successful in modeling the folding landscape. Probabilistic Roadmap Methods ...
Machine Learning Computational Biology Protein Conformation Thermodynamics Movement Proteins Models, Molecular Protein Folding
View on PubMed DOI

Machine Learning: How Much Does It Tell about Protein Folding Rates?

PloS one Nov 25, 2015
The prediction of protein folding rates is a necessary step towards understanding the principles of protein folding. Due to the increasing amount of experimental data, numerous protein folding models and predictors of protein folding rates have been ...
Machine Learning Proteins Reproducibility of Results Protein Folding
View on PubMed DOI

Protein folds recognized by an intelligent predictor based-on evolutionary and structural information.

Journal of computational chemistry Oct 27, 2015
Protein fold recognition is an important and essential step in determining tertiary structure of a protein in biological science. In this study, a model termed NiRecor is developed for recognizing protein folds based on artificial neural networks inc...
Protein Folding Proteins Protein Conformation Computational Biology Evolution, Molecular Neural Networks, Computer
View on PubMed DOI

Accurate contact predictions using covariation techniques and machine learning.

Proteins Aug 14, 2015
Here we present the results of residue-residue contact predictions achieved in CASP11 by the CONSIP2 server, which is based around our MetaPSICOV contact prediction method. On a set of 40 target domains with a median family size of around 40 effectiv...
Sequence Alignment Protein Interaction Domains and Motifs Viruses Protein Structure, Secondary Humans Internet Protein Folding Amino Acid Sequence Computational Biology Software Neural Networks, Computer Models, Statistical Databases, Protein Computer Simulation Proteins Models, Molecular Machine Learning Bacteria
View on PubMed DOI

Machine Learnable Fold Space Representation based on Residue Cluster Classes.

Computational biology and chemistry Jul 30, 2015
MOTIVATION: Protein fold space is a conceptual framework where all possible protein folds exist and ideas about protein structure, function and evolution may be analyzed. Classification of protein folds in this space is commonly achieved by using sim...
Machine Learning Proteins Protein Folding Cluster Analysis
View on PubMed DOI

Types and effects of protein variations.

Human genetics Jan 24, 2015
Variations in proteins have very large number of diverse effects affecting sequence, structure, stability, interactions, activity, abundance and other properties. Although protein-coding exons cover just over 1 % of the human genome they harbor an di...
Amino Acid Sequence Genetic Variation Animals Gene Ontology Protein Processing, Post-Translational Models, Molecular Protein Structure, Quaternary Humans Molecular Dynamics Simulation Databases, Protein Proteins Structure-Activity Relationship Protein Structure, Secondary Protein Folding
View on PubMed DOI

Discrimination of acidic and alkaline enzyme using Chou's pseudo amino acid composition in conjunction with probabilistic neural network model.

Journal of theoretical biology Oct 22, 2014
Enzyme catalysis is one of the most essential and striking processes among of all the complex processes that have evolved in living organisms. Enzymes are biological catalysts, which play a significant role in industrial applications as well as in me...
Protein Folding Enzymes Sequence Analysis, Protein Databases, Protein Models, Chemical Neural Networks, Computer Algorithms
View on PubMed DOI

Investigating the determinants of performance in machine learning for protein fitness prediction.

Protein science : a publication of the Protein Society Aug 1, 2025
Machine learning (ML) has revolutionized protein biology, solving long-standing problems in protein folding, scaffold generation, and function design tasks. A range of architectures have shown success on supervised protein fitness prediction tasks. N...
Protein Folding Algorithms Proteins Machine Learning
View on PubMed DOI

Artificial intelligence and first-principle methods in protein redesign: A marriage of convenience?

Protein science : a publication of the Protein Society Aug 1, 2025
Since AlphaFold2's rise, many deep learning methods for protein design have emerged. Here, we validate widely used and recognized tools, compare them with first-principle methods, and explore their combinations, focusing on their effectiveness in pro...
Artificial Intelligence Deep Learning Protein Conformation Protein Engineering Protein Folding Databases, Protein Models, Molecular Proteins
View on PubMed DOI

Characterization of conformational flexibility in protein structures by applying artificial intelligence to molecular modeling.

Journal of structural biology Jun 1, 2025
Recent AI applications have revolutionized the modeling of structurally unresolved protein regions, thereby complementing traditional computational methods. These state-of-the-art techniques can generate numerous candidate structures, significantly e...
Protein Conformation Protein Folding Proteins Thermodynamics Ubiquitin Artificial Intelligence Models, Molecular Molecular Dynamics Simulation
View on PubMed DOI
Popular Topics
Recent Journals