AIMC Topic: Amino Acid Sequence

Clear Filters Showing 401 to 410 of 694 articles

Unified rational protein engineering with sequence-based deep representation learning.

Nature methods Oct 21, 2019
Rational protein engineering requires a holistic understanding of protein function. Here, we apply deep learning to unlabeled amino-acid sequences to distill the fundamental features of a protein into a statistical representation that is semantically...
Protein Engineering Deep Learning Mutation Amino Acid Sequence Protein Stability
View on PubMed DOI

Computational methods and tools for binding site recognition between proteins and small molecules: from classical geometrical approaches to modern machine learning strategies.

Journal of computer-aided molecular design Oct 18, 2019
In the current "genomic era" the number of identified genes is growing exponentially. However, the biological function of a large number of the corresponding proteins is still unknown. Recognition of small molecule ligands (e.g., substrates, inhibito...
Machine Learning Software Drug Design Humans Artificial Intelligence Models, Molecular Amino Acid Sequence Ligands Protein Binding Computational Biology Proteins Protein Conformation Small Molecule Libraries Sequence Homology
View on PubMed DOI

Uncovering Thousands of New Peptides with Sequence-Mask-Search Hybrid Peptide Sequencing Framework.

Molecular & cellular proteomics : MCP Oct 7, 2019
Typical analyses of mass spectrometry data only identify amino acid sequences that exist in reference databases. This restricts the possibility of discovering new peptides such as those that contain uncharacterized mutations or originate from unexpec...
HLA Antigens Humans Amino Acid Sequence Peptides Tandem Mass Spectrometry Datasets as Topic Deep Learning Sequence Analysis, Protein Phosphopeptides
View on PubMed DOI

One-shot optimization of multiple enzyme parameters: Tailoring glucose oxidase for pH and electron mediators.

Biotechnology and bioengineering Oct 1, 2019
Enzymes are biological catalysts with many industrial applications, but natural enzymes are usually unsuitable for industrial processes because they are not optimized for the process conditions. The properties of enzymes can be improved by directed e...
Kinetics Glucose Nitrosamines Hydrogen-Ion Concentration Directed Molecular Evolution Machine Learning Mutagenesis, Site-Directed Amino Acid Sequence Models, Statistical Ferrous Compounds Mutation Glucose Oxidase
View on PubMed DOI

econvRBP: Improved ensemble convolutional neural networks for RNA binding protein prediction directly from sequence.

Methods (San Diego, Calif.) Sep 9, 2019
RNA binding proteins (RBPs) determine RNA process from synthesis to decay, which play a key role in RNA transport, translation and degradation. Therefore, exploring RBPs' function from the amino acid sequence using computational methods has become on...
Computational Biology Deep Learning RNA-Binding Proteins Sequence Analysis, Protein RNA Amino Acid Sequence Datasets as Topic Binding Sites
View on PubMed DOI

Improvement of Epitope Prediction Using Peptide Sequence Descriptors and Machine Learning.

International journal of molecular sciences Sep 5, 2019
In this work, we improved a previous model used for the prediction of proteomes as new B-cell epitopes in vaccine design. The predicted epitope activity of a queried peptide is based on its sequence, a known reference epitope sequence under specific ...
Amino Acid Sequence Epitope Mapping Peptides ROC Curve Structure-Activity Relationship Humans Machine Learning
View on PubMed DOI

Sequence assignment for low-resolution modelling of protein crystal structures.

Acta crystallographica. Section D, Structural biology Jul 31, 2019
The performance of automated model building in crystal structure determination usually decreases with the resolution of the experimental data, and may result in fragmented models and incorrect side-chain assignment. Presented here are new methods for...
Amino Acid Sequence Molecular Docking Simulation Machine Learning Protein Conformation Software Datasets as Topic Proteins Algorithms Crystallography, X-Ray Databases, Protein
View on PubMed DOI

Prediction of ATP-binding sites in membrane proteins using a two-dimensional convolutional neural network.

Journal of molecular graphics & modelling Jul 15, 2019
Membrane proteins, the most important drug targets, account for around 30% of total proteins encoded by the genome of living organisms. An important role of these proteins is to bind adenosine triphosphate (ATP), facilitating crucial biological proce...
Position-Specific Scoring Matrices Computational Biology Membrane Proteins Models, Theoretical Algorithms Reproducibility of Results ROC Curve Neural Networks, Computer Binding Sites Databases, Protein Amino Acid Motifs Machine Learning Amino Acid Sequence Adenosine Triphosphate Web Browser
View on PubMed DOI

Protein Function Prediction: From Traditional Classifier to Deep Learning.

Proteomics Jul 11, 2019
Deep learning demonstrates greater competence over traditional machine learning techniques for many tasks. In last several years, deep learning has been applied to protein function prediction and a series of good achievements has been obtained. These...
Proteins Amino Acid Sequence Machine Learning Deep Learning Computational Biology
View on PubMed DOI

Learning Compositional Representations of Interacting Systems with Restricted Boltzmann Machines: Comparative Study of Lattice Proteins.

Neural computation Jul 1, 2019
A restricted Boltzmann machine (RBM) is an unsupervised machine learning bipartite graphical model that jointly learns a probability distribution over data and extracts their relevant statistical features. RBMs were recently proposed for characterizi...
Models, Molecular Amino Acid Sequence Probability Static Electricity Stochastic Processes Sequence Alignment Proteins Unsupervised Machine Learning Principal Component Analysis Computer Simulation Models, Statistical
View on PubMed DOI
Popular Topics
Recent Journals