AIMC Topic: Amino Acid Sequence

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Improving Protein Gamma-Turn Prediction Using Inception Capsule Networks.

Scientific reports Oct 24, 2018
Protein gamma-turn prediction is useful in protein function studies and experimental design. Several methods for gamma-turn prediction have been developed, but the results were unsatisfactory with Matthew correlation coefficients (MCC) around 0.2-0.4...
Proteins Amino Acid Sequence Protein Structure, Secondary Neural Networks, Computer Algorithms Computational Biology
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A computational method for prediction of xylanase enzymes activity in strains of Bacillus subtilis based on pseudo amino acid composition features.

PloS one Oct 22, 2018
Xylanases are hydrolytic enzymes which based on physicochemical properties, structure, mode of action and substrate specificities are classified into various glycoside hydrolase (GH) families. The purpose of this study is to show that the activity of...
Machine Learning Temperature Computational Biology Bacillus subtilis Models, Biological Hydrogen-Ion Concentration Amino Acid Sequence Substrate Specificity Endo-1,4-beta Xylanases
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Deep-RBPPred: Predicting RNA binding proteins in the proteome scale based on deep learning.

Scientific reports Oct 15, 2018
RNA binding protein (RBP) plays an important role in cellular processes. Identifying RBPs by computation and experiment are both essential. Recently, an RBP predictor, RBPPred, is proposed in our group to predict RBPs. However, RBPPred is too slow fo...
Neural Networks, Computer Databases, Protein Amino Acid Sequence Sensitivity and Specificity Deep Learning Sequence Analysis, Protein Machine Learning Computational Biology Algorithms RNA-Binding Proteins Proteome
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Effective DNA binding protein prediction by using key features via Chou's general PseAAC.

Journal of theoretical biology Oct 11, 2018
DNA-binding proteins (DBPs) are responsible for several cellular functions, starting from our immunity system to the transport of oxygen. In the recent studies, scientists have used supervised machine learning based methods that use information from ...
Computational Biology Support Vector Machine DNA-Binding Proteins Algorithms Amino Acid Sequence Reproducibility of Results ROC Curve
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Sequence-based analysis and prediction of lantibiotics: A machine learning approach.

Computational biology and chemistry Oct 9, 2018
Lantibiotics, an important group of ribosomally synthesized peptides, represent an important arsenal of novel promising antimicrobials showing high potency in fighting against the prevalence of antibiotic resistance among microbial pathogens. However...
Machine Learning Glutamic Acid Bacteriocins Drug Design Algorithms Amino Acid Sequence Anti-Bacterial Agents Leucine Computer-Aided Design
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DeepNitro: Prediction of Protein Nitration and Nitrosylation Sites by Deep Learning.

Genomics, proteomics & bioinformatics Sep 27, 2018
Protein nitration and nitrosylation are essential post-translational modifications (PTMs) involved in many fundamental cellular processes. Recent studies have revealed that excessive levels of nitration and nitrosylation in some critical proteins are...
Internet Amino Acid Sequence Nitrosation Deep Learning Proteins Amino Acids Neural Networks, Computer Software Reproducibility of Results Humans
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Isolation and identification of immunomodulatory selenium-containing peptides from selenium-enriched rice protein hydrolysates.

Food chemistry Sep 20, 2018
The RAW264.7 cell model was employed to screen immunomodulatory selenium-containing peptides from selenium-enriched rice protein hydrolysates (SPHs). Moreover, the selenium-containing peptides of high-activity protein hydrolysates were purified by Se...
Selenomethionine Sonication Cell Proliferation Selenium RAW 264.7 Cells Amino Acid Sequence Macrophages Mice Oryza Metalloendopeptidases Chromatography, High Pressure Liquid Animals Nitric Oxide Immunologic Factors Protein Hydrolysates Tandem Mass Spectrometry Peptides
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Protein function prediction from protein-protein interaction network using gene ontology based neighborhood analysis and physico-chemical features.

Journal of bioinformatics and computational biology Sep 19, 2018
Protein Function Prediction from Protein-Protein Interaction Network (PPIN) and physico-chemical features using the Gene Ontology (GO) classification are indeed very useful for assigning biological or biochemical functions to a protein. They also lea...
Saccharomyces cerevisiae Gene Ontology Saccharomyces cerevisiae Proteins Proteins Databases, Protein Amino Acid Sequence Humans Protein Interaction Maps Computational Biology
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Extraction, identification and structure-activity relationship of antioxidant peptides from sesame (Sesamum indicum L.) protein hydrolysate.

Food research international (Ottawa, Ont.) Sep 4, 2018
To elucidate the sequence, origin and structure-activity relationship of antioxidant peptides from sesame protein, sesame protein was hydrolysed by a dual-enzyme system comprised alcalase and trypsin, then this hydrolysate was fractionated by ultrafi...
Subtilisins Sulfonic Acids Trypsin Quantitative Structure-Activity Relationship Protein Hydrolysates Antioxidants Sesamum Biphenyl Compounds Picrates Benzothiazoles Seeds Oligopeptides Models, Molecular Amino Acid Sequence
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Predicting improved protein conformations with a temporal deep recurrent neural network.

PloS one Sep 4, 2018
Accurate protein structure prediction from amino acid sequence is still an unsolved problem. The most reliable methods centre on template based modelling. However, the accuracy of these models entirely depends on the availability of experimentally re...
Deep Learning Neural Networks, Computer Sequence Analysis, Protein Molecular Dynamics Simulation Software Protein Conformation Amino Acid Sequence Protein Folding Algorithms
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