AIMC Topic: Proteins

Clear Filters Showing 1091 to 1100 of 1970 articles

Hidden bias in the DUD-E dataset leads to misleading performance of deep learning in structure-based virtual screening.

PloS one Aug 20, 2019
Recently much effort has been invested in using convolutional neural network (CNN) models trained on 3D structural images of protein-ligand complexes to distinguish binding from non-binding ligands for virtual screening. However, the dearth of reliab...
Drug Evaluation, Preclinical Proteins Deep Learning Ligands Pharmaceutical Preparations User-Computer Interface Databases, Pharmaceutical
View on PubMed DOI

rawMSA: End-to-end Deep Learning using raw Multiple Sequence Alignments.

PloS one Aug 15, 2019
In the last decades, huge efforts have been made in the bioinformatics community to develop machine learning-based methods for the prediction of structural features of proteins in the hope of answering fundamental questions about the way proteins fun...
Proteins Deep Learning Sequence Alignment Computational Biology
View on PubMed DOI

Protein secondary structure prediction using neural networks and deep learning: A review.

Computational biology and chemistry Aug 12, 2019
Literature contains over fifty years of accumulated methods proposed by researchers for predicting the secondary structures of proteins in silico. A large part of this collection is comprised of artificial neural network-based approaches, a field of ...
Proteins Protein Structure, Secondary Deep Learning
View on PubMed DOI

PaleAle 5.0: prediction of protein relative solvent accessibility by deep learning.

Amino acids Aug 6, 2019
Predicting the three-dimensional structure of proteins is a long-standing challenge of computational biology, as the structure (or lack of a rigid structure) is well known to determine a protein's function. Predicting relative solvent accessibility (...
Entropy Deep Learning Protein Structure, Secondary Amino Acids Evolution, Chemical Software Solvents Algorithms Computational Biology Proteins
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...
Machine Learning Amino Acid Sequence Molecular Docking Simulation Proteins Crystallography, X-Ray Protein Conformation Software Databases, Protein Datasets as Topic Algorithms
View on PubMed DOI

Protein secondary structure detection in intermediate-resolution cryo-EM maps using deep learning.

Nature methods Jul 29, 2019
Although structures determined at near-atomic resolution are now routinely reported by cryo-electron microscopy (cryo-EM), many density maps are determined at an intermediate resolution, and extracting structure information from these maps is still a...
Models, Molecular Cryoelectron Microscopy Protein Structure, Secondary Deep Learning Proteins Neural Networks, Computer Software Humans
View on PubMed DOI

Using deep maxout neural networks to improve the accuracy of function prediction from protein interaction networks.

PloS one Jul 23, 2019
Protein-protein interaction network data provides valuable information that infers direct links between genes and their biological roles. This information brings a fundamental hypothesis for protein function prediction that interacting proteins tend ...
Protein Interaction Mapping Computational Biology Proteins Humans Neural Networks, Computer Protein Interaction Maps
View on PubMed DOI

Artificial Intelligence Approach to Find Lead Compounds for Treating Tumors.

The journal of physical chemistry letters Jul 22, 2019
It has been demonstrated that MMP13 enzyme is related to most cancer cell tumors. The world's largest traditional Chinese medicine database was applied to screen for structure-based drug design and ligand-based drug design. To predict drug activity, ...
Antineoplastic Agents Deep Learning Cyclin-Dependent Kinase Inhibitor p16 Peptides Drug Design Models, Molecular Mutation Ligands Proteins Databases, Protein Machine Learning Algorithms Databases, Pharmaceutical Matrix Metalloproteinase 13 Binding Sites Proto-Oncogene Proteins c-mdm2 Cyclin-Dependent Kinase 6 Proto-Oncogene Proteins c-bcl-2 Tumor Suppressor Protein p53
View on PubMed DOI

Accurate prediction of potential druggable proteins based on genetic algorithm and Bagging-SVM ensemble classifier.

Artificial intelligence in medicine Jul 19, 2019
Discovering and accurately locating drug targets is of great significance for the research and development of new drugs. As a different approach to traditional drug development, the machine learning algorithm is used to predict the drug target by min...
Drug Development Support Vector Machine Molecular Targeted Therapy Proteins Humans Algorithms
View on PubMed DOI

Analysis of Protein-Protein Functional Associations by Using Gene Ontology and KEGG Pathway.

BioMed research international Jul 18, 2019
Protein-protein interaction (PPI) plays an extremely remarkable role in the growth, reproduction, and metabolism of all lives. A thorough investigation of PPI can uncover the mechanism of how proteins express their functions. In this study, we used g...
Computational Biology Genes, Essential Gene Ontology Proteins Databases, Protein
View on PubMed DOI
Popular Topics
Recent Journals