AIMC Topic: Proteins

Clear Filters Showing 1251 to 1260 of 1984 articles

ProLanGO: Protein Function Prediction Using Neural Machine Translation Based on a Recurrent Neural Network.

Molecules (Basel, Switzerland) Oct 17, 2017
With the development of next generation sequencing techniques, it is fast and cheap to determine protein sequences but relatively slow and expensive to extract useful information from protein sequences because of limitations of traditional biological...
Reproducibility of Results Computational Biology Proteins Databases, Protein Gene Ontology Machine Learning Software Algorithms Neural Networks, Computer
View on PubMed DOI

Systematic Identification of Machine-Learning Models Aimed to Classify Critical Residues for Protein Function from Protein Structure.

Molecules (Basel, Switzerland) Oct 9, 2017
Protein structure and protein function should be related, yet the nature of this relationship remains unsolved. Mapping the critical residues for protein function with protein structure features represents an opportunity to explore this relationship,...
Machine Learning Algorithms Protein Conformation Proteins Structure-Activity Relationship Models, Molecular
View on PubMed DOI

HashGO: hashing gene ontology for protein function prediction.

Computational biology and chemistry Oct 4, 2017
Gene ontology (GO) is a standardized and controlled vocabulary of terms that describe the molecular functions, biological roles and cellular locations of proteins. GO terms and GO hierarchy are regularly updated as the accumulated biological knowledg...
Gene Ontology Proteins Databases, Protein Humans
View on PubMed DOI

Manipulation of Biomolecule-Modified Liquid-Metal Blobs.

Angewandte Chemie (International ed. in English) Oct 2, 2017
Soft and deformable liquid metals (LMs) are building components in various systems related to uncertain and dynamic task environments. Herein we describe the development of a biomolecule-triggered external-manipulation method involving LM conjugates ...
Humans Animals Bioengineering Biomedical Engineering HT29 Cells Serum Albumin, Bovine Antibodies Motion Catalase Adsorption Cattle Sulfhydryl Compounds Proteins Metals Biocompatible Materials Robotics Biocatalysis
View on PubMed DOI

Demystifying Multitask Deep Neural Networks for Quantitative Structure-Activity Relationships.

Journal of chemical information and modeling Oct 2, 2017
Deep neural networks (DNNs) are complex computational models that have found great success in many artificial intelligence applications, such as computer vision1,2 and natural language processing.3,4 In the past four years, DNNs have also generated p...
Neural Networks, Computer Proteins Models, Chemical Quantitative Structure-Activity Relationship Artificial Intelligence Computer Simulation Drug Delivery Systems
View on PubMed DOI

Improved protein contact predictions with the MetaPSICOV2 server in CASP12.

Proteins Sep 29, 2017
In this paper, we present the results for the MetaPSICOV2 contact prediction server in the CASP12 community experiment (http://predictioncenter.org). Over the 35 assessed Free Modelling target domains the MetaPSICOV2 server achieved a mean precision ...
Protein Interaction Domains and Motifs Computational Biology Proteins Models, Molecular Internet Crystallography, X-Ray Protein Conformation Machine Learning Humans Software Neural Networks, Computer Algorithms
View on PubMed DOI

Revealing protein functions based on relationships of interacting proteins and GO terms.

Journal of biomedical semantics Sep 20, 2017
BACKGROUND: In recent years, numerous computational methods predicted protein function based on the protein-protein interaction (PPI) network. These methods supposed that two proteins share the same function if they interact with each other. However,...
Saccharomyces cerevisiae Proteins Proteins Protein Interaction Maps Databases, Protein Computational Biology Gene Ontology
View on PubMed DOI

Factors analysis of protein O-glycosylation site prediction.

Computational biology and chemistry Sep 18, 2017
To improve the prediction accuracy of O-glycosylation sites, and analyze the structure of the O-glycosylation sites, factor analysis based prediction is proposed in this study. Our studies show that factor analysis strongly boosts machine learning al...
Discriminant Analysis Databases, Protein Machine Learning Principal Component Analysis Algorithms Glycosylation Proteins
View on PubMed DOI

Convex-PL: a novel knowledge-based potential for protein-ligand interactions deduced from structural databases using convex optimization.

Journal of computer-aided molecular design Sep 18, 2017
We present a novel optimization approach to train a free-shape distance-dependent protein-ligand scoring function called Convex-PL. We do not impose any functional form of the scoring function. Instead, we decompose it into a polynomial basis and ded...
Structure-Activity Relationship Molecular Structure Knowledge Bases Ligands Protein Conformation Humans Binding Sites Machine Learning Algorithms Molecular Docking Simulation Protein Binding Drug Design Proteins Databases, Protein
View on PubMed DOI

Deep learning methods for protein torsion angle prediction.

BMC bioinformatics Sep 18, 2017
BACKGROUND: Deep learning is one of the most powerful machine learning methods that has achieved the state-of-the-art performance in many domains. Since deep learning was introduced to the field of bioinformatics in 2012, it has achieved success in a...
Neural Networks, Computer Machine Learning Proteins Molecular Structure Protein Structure, Secondary
View on PubMed DOI
Popular Topics
Recent Journals