AIMC Topic: Proteins

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A gene prioritization method based on a swine multi-omics knowledgebase and a deep learning model.

Communications biology Sep 10, 2020
The analyses of multi-omics data have revealed candidate genes for objective traits. However, they are integrated poorly, especially in non-model organisms, and they pose a great challenge for prioritizing candidate genes for follow-up experimental v...
Proteins Swine Transcriptome Genomics Databases, Genetic Deep Learning Neural Networks, Computer Animals
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Discovering Protein Conformational Flexibility through Artificial-Intelligence-Aided Molecular Dynamics.

The journal of physical chemistry. B Sep 9, 2020
Proteins sample a variety of conformations distinct from their crystal structure. These structures, their propensities, and the pathways for moving between them contain an enormous amount of information about protein function that is hidden from a pu...
Protein Conformation Artificial Intelligence Proteins Intelligence Molecular Dynamics Simulation Humans
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ODiNPred: comprehensive prediction of protein order and disorder.

Scientific reports Sep 8, 2020
Structural disorder is widespread in eukaryotic proteins and is vital for their function in diverse biological processes. It is therefore highly desirable to be able to predict the degree of order and disorder from amino acid sequence. It is, however...
Intrinsically Disordered Proteins Protein Folding Models, Molecular Amino Acids Algorithms Computational Biology Proteins Databases, Protein Neural Networks, Computer Software Humans
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Machine learning techniques for sequence-based prediction of viral-host interactions between SARS-CoV-2 and human proteins.

Biomedical journal Sep 3, 2020
BACKGROUND: COVID-19 (Coronavirus Disease-19), a disease caused by the SARS-CoV-2 virus, has been declared as a pandemic by the World Health Organization on March 11, 2020. Over 15 million people have already been affected worldwide by COVID-19, resu...
Machine Learning COVID-19 SARS-CoV-2 Proteins Humans Sequence Analysis Host Microbial Interactions
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Pain-CKB, A Pain-Domain-Specific Chemogenomics Knowledgebase for Target Identification and Systems Pharmacology Research.

Journal of chemical information and modeling Sep 2, 2020
A traditional single-target analgesic, though it may be highly selective and potent, may not be sufficient to mitigate pain. An alternative strategy for alleviation of pain is to seek simultaneous modulation at multiple nodes in the network of pain-s...
Proteins Pain Knowledge Bases Humans
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ivis Dimensionality Reduction Framework for Biomacromolecular Simulations.

Journal of chemical information and modeling Sep 1, 2020
Molecular dynamics (MD) simulations have been widely applied to study macromolecules including proteins. However, the high dimensionality of the data sets produced by simulations makes thorough analysis difficult and further hinders a deeper understa...
Proteins Principal Component Analysis Neural Networks, Computer Molecular Dynamics Simulation
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A novel fusion based on the evolutionary features for protein fold recognition using support vector machines.

Scientific reports Sep 1, 2020
Protein fold recognition plays a crucial role in discovering three-dimensional structure of proteins and protein functions. Several approaches have been employed for the prediction of protein folds. Some of these approaches are based on extracting fe...
Evolution, Molecular Proteins Databases, Protein Computational Biology Support Vector Machine Sequence Analysis, Protein Amino Acid Sequence Protein Folding
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HybridSucc: A Hybrid-learning Architecture for General and Species-specific Succinylation Site Prediction.

Genomics, proteomics & bioinformatics Aug 28, 2020
As an important protein acylation modification, lysine succinylation (Ksucc) is involved in diverse biological processes, and participates in human tumorigenesis. Here, we collected 26,243 non-redundant known Ksucc sites from 13 species as the benchm...
Lysine Succinic Acid Amino Acid Sequence Species Specificity Acylation ROC Curve Proteome Proteins Area Under Curve Algorithms Neoplasms Humans Machine Learning
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Prediction of antioxidant proteins using hybrid feature representation method and random forest.

Genomics Aug 17, 2020
Natural antioxidant proteins are mainly found in plants and animals, which interact to eliminate excessive free radicals and protect cells and DNA from damage, prevent and treat some diseases. Therefore, accurate identification of antioxidant protein...
Antioxidants Proteins Sequence Analysis, Protein Machine Learning
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Data Set Augmentation Allows Deep Learning-Based Virtual Screening to Better Generalize to Unseen Target Classes and Highlight Important Binding Interactions.

Journal of chemical information and modeling Aug 4, 2020
Current deep learning methods for structure-based virtual screening take the structures of both the protein and the ligand as input but make little or no use of the protein structure when predicting ligand binding. Here, we show how a relatively simp...
Ligands Deep Learning Proteins
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