AIMC Topic: Sequence Analysis, Protein

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PFP-WGAN: Protein function prediction by discovering Gene Ontology term correlations with generative adversarial networks.

PloS one Feb 25, 2021
Understanding the functionality of proteins has emerged as a critical problem in recent years due to significant roles of these macro-molecules in biological mechanisms. However, in-laboratory techniques for protein function prediction are not as eff...
Computational Biology Proteins Gene Ontology Humans Gene Regulatory Networks Sequence Analysis, Protein
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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 Humans Proteins Software Databases, Protein Research Design Deep Learning Protein Binding Benchmarking Protein Conformation Binding Sites Sequence Alignment Sequence Analysis, Protein Protein Interaction Domains and Motifs
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CrystalM: A Multi-View Fusion Approach for Protein Crystallization Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Feb 3, 2021
Improving the accuracy of predicting protein crystallization is very important for protein crystallization projects, which is a critical step for the determination of protein structure by X-ray crystallography. At present, many machine learning metho...
Support Vector Machine Computational Biology Models, Statistical Proteins Crystallization Sequence Analysis, Protein Position-Specific Scoring Matrices
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Template-based prediction of protein structure with deep learning.

BMC genomics Dec 29, 2020
BACKGROUND: Accurate prediction of protein structure is fundamentally important to understand biological function of proteins. Template-based modeling, including protein threading and homology modeling, is a popular method for protein tertiary struct...
Proteins Databases, Protein Protein Conformation Algorithms Deep Learning Sequence Analysis, Protein Software
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Noninvasive diagnostic of periprosthetic joint infection by urinary peptide markers: A preliminary study.

Journal of orthopaedic research : official publication of the Orthopaedic Research Society Nov 25, 2020
Previous immunohistochemical analyses revealed altered protein expression in the periprosthetic membranes of patients with periprosthetic joint infection (PJI). Proteins are degraded to peptides that may pass the blood-kidney barrier depending on the...
Prosthesis-Related Infections Sequence Analysis, Protein Support Vector Machine Peptide Hydrolases Humans Biomarkers Aged Peptides Proteome
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ReFold-MAP: Protein remote homology detection and fold recognition based on features extracted from profiles.

Analytical biochemistry Nov 6, 2020
Protein remote homology detection and protein fold recognition are two important tasks in protein structure and function prediction. There are three kinds of methods in this field, including the discriminative methods, the alignment methods, and the ...
Proteins Databases, Protein Protein Folding Sequence Alignment Sequence Analysis, Protein Artificial Intelligence
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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...
Sequence Analysis, Protein Databases, Protein Amino Acid Sequence Protein Folding Computational Biology Evolution, Molecular Proteins Support Vector Machine
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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...
Machine Learning Antioxidants Proteins Sequence Analysis, Protein
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cnnAlpha: Protein disordered regions prediction by reduced amino acid alphabets and convolutional neural networks.

Proteins Aug 7, 2020
Intrinsically disordered regions (IDR) play an important role in key biological processes and are closely related to human diseases. IDRs have great potential to serve as targets for drug discovery, most notably in disordered binding regions. Accurat...
Datasets as Topic Intrinsically Disordered Proteins Sequence Analysis, Protein Multifactor Dimensionality Reduction Benchmarking Amino Acid Sequence Data Mining Computational Biology Area Under Curve Neural Networks, Computer Machine Learning ROC Curve Humans
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Machine-learning approach expands the repertoire of anti-CRISPR protein families.

Nature communications Jul 29, 2020
The CRISPR-Cas are adaptive bacterial and archaeal immunity systems that have been harnessed for the development of powerful genome editing and engineering tools. In the incessant host-parasite arms race, viruses evolved multiple anti-defense mechani...
Gene Editing Computational Biology Archaea Host-Parasite Interactions CRISPR-Cas Systems Machine Learning Bacteriophages Datasets as Topic Bacteria Viral Proteins Sequence Analysis, Protein Sequence Homology, Amino Acid CRISPR-Associated Protein 9
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