AIMC Topic: Tyrosine

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Stacking based ensemble learning framework for identification of nitrotyrosine sites.

Computers in biology and medicine Oct 3, 2024
Protein nitrotyrosine is an essential post-translational modification that results from the nitration of tyrosine amino acid residues. This modification is known to be associated with the regulation and characterization of several biological function...
Humans Machine Learning Software Proteins Databases, Protein Tyrosine Algorithms Computational Biology Protein Processing, Post-Translational
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Machine learning-powered wearable interface for distinguishable and predictable sweat sensing.

Biosensors & bioelectronics Aug 28, 2024
The constrained resources on wearable devices pose a challenge in meeting the demands for comprehensive sensing information, and current wearable non-enzymatic sensors face difficulties in achieving specific detection in biofluids. To address this is...
Wearable Electronic Devices Humans Hydrogen-Ion Concentration Biosensing Techniques Machine Learning Electrodes Equipment Design Biomarkers Tryptophan Tyrosine Sweat Wireless Technology
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Determination of monophenolase activity based on backpropagation neural network analysis of three-dimensional fluorescence spectroscopy.

Journal of biotechnology Feb 10, 2023
Tyrosinase is pivotal for melanin formation. Measuring monophenolase activity is of great importance for both fundamental research and industrial applications. For the first time, a backpropagation (BP) artificial neural network with three-dimensiona...
Monophenol Monooxygenase Neural Networks, Computer Tyrosine Spectrometry, Fluorescence
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Selective Inhibitor Design for Kinase Homologs Using Multiobjective Monte Carlo Tree Search.

Journal of chemical information and modeling Nov 5, 2022
Designing highly selective molecules for a drug target protein is a challenging task in drug discovery. This task can be regarded as a multiobjective problem that simultaneously satisfies criteria for various objectives, such as selectivity for a tar...
Tyrosine Artificial Intelligence Drug Design Monte Carlo Method
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Deep learning study of tyrosine reveals that roaming can lead to photodamage.

Nature chemistry Jun 2, 2022
Amino acids are among the building blocks of life, forming peptides and proteins, and have been carefully 'selected' to prevent harmful reactions caused by light. To prevent photodamage, molecules relax from electronic excited states to the ground st...
Quantum Theory Tyrosine Photochemistry Deep Learning Amino Acids
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PredNTS: Improved and Robust Prediction of Nitrotyrosine Sites by Integrating Multiple Sequence Features.

International journal of molecular sciences Mar 8, 2021
Nitrotyrosine, which is generated by numerous reactive nitrogen species, is a type of protein post-translational modification. Identification of site-specific nitration modification on tyrosine is a prerequisite to understanding the molecular functio...
Sequence Analysis, Protein Machine Learning Computational Biology Support Vector Machine Protein Processing, Post-Translational Proteins Tyrosine
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Machine learning-based differentiation between multiple sclerosis and glioma WHO II°-IV° using O-(2-[18F] fluoroethyl)-L-tyrosine positron emission tomography.

Journal of neuro-oncology Jan 27, 2021
INTRODUCTION: This study aimed to test the diagnostic significance of FET-PET imaging combined with machine learning for the differentiation between multiple sclerosis (MS) and glioma II°-IV°.
Multiple Sclerosis Image Interpretation, Computer-Assisted Tyrosine Aged Radiopharmaceuticals Adult Positron-Emission Tomography Brain Neoplasms Male Middle Aged Glioma Humans Machine Learning Female
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Approximating anatomically-guided PET reconstruction in image space using a convolutional neural network.

NeuroImage Sep 21, 2020
In the last two decades, it has been shown that anatomically-guided PET reconstruction can lead to improved bias-noise characteristics in brain PET imaging. However, despite promising results in simulations and first studies, anatomically-guided PET ...
Neural Networks, Computer Brain Image Processing, Computer-Assisted Magnetic Resonance Imaging Radiopharmaceuticals Positron-Emission Tomography Humans Fluorodeoxyglucose F18 Tyrosine Nortropanes
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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...
Automation Tyrosine Amino Acid Sequence Nitrates Protein Processing, Post-Translational Discriminant Analysis Supervised Machine Learning Peptides
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Boosting phosphorylation site prediction with sequence feature-based machine learning.

Proteins Aug 22, 2019
Protein phosphorylation is one of the essential posttranslation modifications playing a vital role in the regulation of many fundamental cellular processes. We propose a LightGBM-based computational approach that uses evolutionary, geometric, sequenc...
Tyrosine Binding Sites Serine Protein Conformation Computational Biology Species Specificity Protein Processing, Post-Translational Proteins Databases, Protein Sequence Analysis, Protein Phosphorylation Algorithms Models, Molecular Threonine Reproducibility of Results Humans Animals Machine Learning
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