AIMC Topic: Proteins

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Infrared Metasurface Augmented by Deep Learning for Monitoring Dynamics between All Major Classes of Biomolecules.

Advanced materials (Deerfield Beach, Fla.) Feb 22, 2021
Insights into the fascinating molecular world of biological processes are crucial for understanding diseases, developing diagnostics, and effective therapeutics. These processes are complex as they involve interactions between four major classes of b...
Spectrophotometry, Infrared Infrared Rays Lab-On-A-Chip Devices Nucleotides Liposomes Deep Learning Nucleic Acids Proteins Sucrose
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Machine learning classifiers aid virtual screening for efficient design of mini-protein therapeutics.

Bioorganic & medicinal chemistry letters Feb 18, 2021
De novo design of mini-proteins (4-12 kDa) has recently been shown to produce new candidates for protein therapeutics. They are temperature stable molecules that bind to the drug target with high affinity for inhibiting its interactions. The developm...
Ligands Small Molecule Libraries Machine Learning Proteins
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Combination of deep neural network with attention mechanism enhances the explainability of protein contact prediction.

Proteins Feb 16, 2021
Deep learning has emerged as a revolutionary technology for protein residue-residue contact prediction since the 2012 CASP10 competition. Considerable advancements in the predictive power of the deep learning-based contact predictions have been achie...
Computational Biology Proteins Databases, Protein Research Design Deep Learning Protein Binding Sequence Alignment Sequence Analysis, Protein Protein Interaction Domains and Motifs Benchmarking Protein Conformation Binding Sites Humans Software
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[A giant step towards elucidating the function of proteins].

Medecine sciences : M/S Feb 16, 2021
Artificial Intelligence Algorithms Deep Learning Proteins Crystallography Protein Folding Protein Structure, Tertiary Myoglobin Caspases X-Ray Diffraction Caspase 1
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CASSPER is a semantic segmentation-based particle picking algorithm for single-particle cryo-electron microscopy.

Communications biology Feb 15, 2021
Particle identification and selection, which is a prerequisite for high-resolution structure determination of biological macromolecules via single-particle cryo-electron microscopy poses a major bottleneck for automating the steps of structure determ...
Protein Conformation Single Molecule Imaging Cryoelectron Microscopy Models, Molecular Semantics Humans Animals Deep Learning Image Processing, Computer-Assisted Proteins
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Convolutional Neural Network-Based Artificial Intelligence for Classification of Protein Localization Patterns.

Biomolecules Feb 11, 2021
Identifying localization of proteins and their specific subpopulations associated with certain cellular compartments is crucial for understanding protein function and interactions with other macromolecules. Fluorescence microscopy is a powerful metho...
Subcellular Fractions Humans Neural Networks, Computer Deep Learning Cell Line Proteins Microscopy, Fluorescence
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Systematic auditing is essential to debiasing machine learning in biology.

Communications biology Feb 10, 2021
Biases in data used to train machine learning (ML) models can inflate their prediction performance and confound our understanding of how and what they learn. Although biases are common in biological data, systematic auditing of ML models to identify ...
Proteins Databases, Protein Bias Proteomics Proteome Pharmaceutical Preparations Data Mining Histocompatibility Antigens Humans Machine Learning Reproducibility of Results Animals Protein Interaction Maps Protein Binding
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OctSurf: Efficient hierarchical voxel-based molecular surface representation for protein-ligand affinity prediction.

Journal of molecular graphics & modelling Feb 9, 2021
Voxel-based 3D convolutional neural networks (CNNs) have been applied to predict protein-ligand binding affinity. However, the memory usage and computation cost of these voxel-based approaches increase cubically with respect to spatial resolution and...
Protein Binding Proteins Ligands Neural Networks, Computer
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In silico design of novel aptamers utilizing a hybrid method of machine learning and genetic algorithm.

Molecular diversity Feb 7, 2021
Aptamers can be regarded as efficient substitutes for monoclonal antibodies in many diagnostic and therapeutic applications. Due to the tedious and prohibitive nature of SELEX (systematic evolution of ligands by exponential enrichment), the in silico...
Machine Learning Algorithms Biomarkers RNA Ligands Molecular Conformation CD13 Antigens Aptamers, Nucleotide Proteins Molecular Dynamics Simulation Molecular Docking Simulation Drug Design
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OCLSTM: Optimized convolutional and long short-term memory neural network model for protein secondary structure prediction.

PloS one Feb 3, 2021
Protein secondary structure prediction is extremely important for determining the spatial structure and function of proteins. In this paper, we apply an optimized convolutional neural network and long short-term memory neural network models to protei...
Proteins Bayes Theorem Protein Structure, Secondary Neural Networks, Computer Computational Biology
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