AIMC Topic: Amino Acid Sequence

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Convolutional Neural Network Based Approach to in Silico Non-Anticipating Prediction of Antigenic Distance for Influenza Virus.

Viruses Sep 12, 2020
Evaluation of the antigenic similarity degree between the strains of the influenza virus is highly important for vaccine production. The conventional method used to measure such a degree is related to performing the immunological assays of hemaggluti...
Amino Acid Sequence Influenza, Human Influenza A Virus, H1N1 Subtype Orthomyxoviridae Antigens, Viral Hemagglutinin Glycoproteins, Influenza Virus Humans Neural Networks, Computer Computer Simulation
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ICTC-RAAC: An improved web predictor for identifying the types of ion channel-targeted conotoxins by using reduced amino acid cluster descriptors.

Computational biology and chemistry Sep 7, 2020
Conotoxins are small peptide toxins which are rich in disulfide and have the unique diversity of sequences. It is significant to correctly identify the types of ion channel-targeted conotoxins because that they are considered as the optimal pharmacol...
Databases, Protein Amino Acids Internet Computational Biology Support Vector Machine Amino Acid Sequence Ion Channels Conotoxins
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Effect of sequence padding on the performance of deep learning models in archaeal protein functional prediction.

Scientific reports Sep 3, 2020
The use of raw amino acid sequences as input for deep learning models for protein functional prediction has gained popularity in recent years. This scheme obliges to manage proteins with different lengths, while deep learning models require same-shap...
Archaeal Proteins Deep Learning Amino Acid Sequence Archaea
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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...
Computational Biology Support Vector Machine Evolution, Molecular Proteins Databases, Protein Amino Acid Sequence Protein Folding Sequence Analysis, Protein
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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...
Proteins Neoplasms Acylation Area Under Curve Species Specificity ROC Curve Amino Acid Sequence Humans Lysine Proteome Machine Learning Succinic Acid Algorithms
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Comprehensive Prediction of Molecular Recognition in a Combinatorial Chemical Space Using Machine Learning.

ACS combinatorial science Aug 17, 2020
In combinatorial chemical approaches, optimizing the composition and arrangement of building blocks toward a particular function has been done using a number of methods, including high throughput molecular screening, molecular evolution, and computat...
Ligands High-Throughput Screening Assays Combinatorial Chemistry Techniques Models, Molecular Molecular Structure Amino Acid Sequence Machine Learning Peptides Protein Binding Peptide Library Structure-Activity Relationship
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The use of knowledge management tools in viroinformatics. Example study of a highly conserved sequence motif in Nsp3 of SARS-CoV-2 as a therapeutic target.

Computers in biology and medicine Aug 13, 2020
Knowledge management tools that assist in systematic review and exploration of scientific knowledge generally are of obvious potential importance in evidence based medicine in general, but also to the design of therapeutics based on the protein subse...
Pandemics COVID-19 SARS-CoV-2 Computational Biology Drug Development Amino Acid Sequence Humans Artificial Intelligence Coronavirus Papain-Like Proteases Conserved Sequence Betacoronavirus Coronavirus Infections Pneumonia, Viral Viral Nonstructural Proteins Binding Sites
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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 Benchmarking Amino Acid Sequence Data Mining Multifactor Dimensionality Reduction ROC Curve Computational Biology Humans Area Under Curve Neural Networks, Computer Machine Learning
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rPTMDetermine: A Fully Automated Methodology for Endogenous Tyrosine Nitration Validation, Site-Localization, and Beyond.

Analytical chemistry Jul 21, 2020
We present herein rPTMDetermine, an adaptive and fully automated methodology for validation of the identification of rarely occurring post-translational modifications (PTMs), using a semisupervised approach with a linear discriminant analysis (LDA) a...
Discriminant Analysis Supervised Machine Learning Amino Acid Sequence Peptides Protein Processing, Post-Translational Nitrates Automation Tyrosine
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Identification of ligand-binding residues using protein sequence profile alignment and query-specific support vector machine model.

Analytical biochemistry Jul 2, 2020
Information embedded in ligand-binding residues (LBRs) of proteins is important for understanding protein functions. How to accurately identify the potential ligand-binding residues is still a challenging problem, especially only protein sequence is ...
Binding Sites Protein Binding Support Vector Machine Proteins Databases, Protein Amino Acid Sequence Ligands
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