AIMC Topic: Proteins

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DeepSuccinylSite: a deep learning based approach for protein succinylation site prediction.

BMC bioinformatics Apr 23, 2020
BACKGROUND: Protein succinylation has recently emerged as an important and common post-translation modification (PTM) that occurs on lysine residues. Succinylation is notable both in its size (e.g., at 100 Da, it is one of the larger chemical PTMs) a...
Deep Learning Protein Processing, Post-Translational Binding Sites Succinates Citric Acid Cycle Proteins Lysine
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Recent advances in robotic protein sample preparation for clinical analysis and other biomedical applications.

Clinica chimica acta; international journal of clinical chemistry Apr 17, 2020
Discovery of new protein biomarker candidates has become a major research goal in the areas of clinical chemistry, analytical chemistry, and biomedicine. These important species constitute the molecular target when it comes to diagnosis, prognosis, a...
Chemistry Techniques, Analytical Analytic Sample Preparation Methods Proteins Robotics Humans
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Machine Learning Approaches for Quality Assessment of Protein Structures.

Biomolecules Apr 17, 2020
Protein structures play a very important role in biomedical research, especially in drug discovery and design, which require accurate protein structures in advance. However, experimental determinations of protein structure are prohibitively costly an...
Proteins Machine Learning Humans Models, Molecular Neural Networks, Computer Bayes Theorem Amino Acid Sequence Support Vector Machine
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Predicting protein-peptide binding sites with a deep convolutional neural network.

Journal of theoretical biology Apr 13, 2020
MOTIVATION: Interactions between proteins and peptides influence biological functions. Predicting such bio-molecular interactions can lead to faster disease prevention and help in drug discovery. Experimental methods for determining protein-peptide b...
Protein Binding Proteins Binding Sites Neural Networks, Computer Peptides
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Deep Generative Models for 3D Linker Design.

Journal of chemical information and modeling Apr 2, 2020
Rational compound design remains a challenging problem for both computational methods and medicinal chemists. Computational generative methods have begun to show promising results for the design problem. However, they have not yet used the power of t...
Machine Learning Models, Molecular Algorithms Proteins
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Big data and artificial intelligence discover novel drugs targeting proteins without 3D structure and overcome the undruggable targets.

Stroke and vascular neurology Mar 29, 2020
The discovery of targeted drugs heavily relies on three-dimensional (3D) structures of target proteins. When the 3D structure of a protein target is unknown, it is very difficult to design its corresponding targeted drugs. Although the 3D structures ...
Molecular Targeted Therapy Protein Conformation Molecular Structure Pharmaceutical Preparations Data Mining Ligands Databases, Protein Structure-Activity Relationship Big Data Proteins Artificial Intelligence Humans Animals Drug Design Computer-Aided Design Drug Discovery
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Improving detection of protein-ligand binding sites with 3D segmentation.

Scientific reports Mar 19, 2020
In recent years machine learning (ML) took bio- and cheminformatics fields by storm, providing new solutions for a vast repertoire of problems related to protein sequence, structure, and interactions analysis. ML techniques, deep neural networks espe...
Binding Sites Drug Discovery Software Proteins Protein Binding Neural Networks, Computer Ligands Drug Design Machine Learning
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DeeplyTough: Learning Structural Comparison of Protein Binding Sites.

Journal of chemical information and modeling Mar 18, 2020
Protein pocket matching, or binding site comparison, is of importance in drug discovery. Identification of similar binding pockets can help guide efforts for hit-finding, understanding polypharmacology, and characterization of protein function. The d...
Algorithms Protein Binding Binding Sites Proteins Neural Networks, Computer
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Advances in Quantitative Bioimage Analysis for Proteins and Cells.

Cytometry. Part A : the journal of the International Society for Analytical Cytology Mar 18, 2020
Artificial Intelligence Proteins Pattern Recognition, Automated Humans
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A deep learning-based method for drug-target interaction prediction based on long short-term memory neural network.

BMC medical informatics and decision making Mar 18, 2020
BACKGROUND: The key to modern drug discovery is to find, identify and prepare drug molecular targets. However, due to the influence of throughput, precision and cost, traditional experimental methods are difficult to be widely used to infer these pot...
Pharmaceutical Preparations Proteins Principal Component Analysis Neural Networks, Computer Deep Learning Humans Drug Development
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