AIMC Topic: Cysteine
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Prediction and analysis of redox-sensitive cysteines using machine learning and statistical methods.
Biological chemistry
Jan 6, 2021
Reactive oxygen species are produced by a number of stimuli and can lead both to irreversible intracellular damage and signaling through reversible post-translational modification. It is unclear which factors contribute to the sensitivity of cysteine...
Deep learning based prediction of species-specific protein S-glutathionylation sites.
Biochimica et biophysica acta. Proteins and proteomics
Mar 29, 2020
As a widespread and reversible post-translational modification of proteins, S-glutathionylation specifically generates the mixed disulfides between cysteine residues and glutathione, which regulates various biological processes including oxidative st...
Dose independent characterization of renal stones by means of dual energy computed tomography and machine learning: an ex-vivo study.
European radiology
Nov 26, 2019
OBJECTIVES: To predict the main component of pure and mixed kidney stones using dual-energy computed tomography and machine learning.
Exploring the limitations of biophysical propensity scales coupled with machine learning for protein sequence analysis.
Scientific reports
Nov 15, 2019
Machine learning (ML) is ubiquitous in bioinformatics, due to its versatility. One of the most crucial aspects to consider while training a ML model is to carefully select the optimal feature encoding for the problem at hand. Biophysical propensity s...
Rapid Identification of Disulfide Bonds and Cysteine-Related Variants in an IgG1 Knob-into-Hole Bispecific Antibody Enhanced by Machine Learning.
Analytical chemistry
Dec 14, 2018
Bispecific antibodies are regarded as the next generation of therapeutic modalities as they can simultaneously bind multiple targets, increasing the efficacy of treatments for several diseases and opening up previously unattainable treatment designs....
A prospective study evaluating impact on renal function following percutaneous nephrolithotomy using Tc99m ethylenedicysteine renal scan: Does multiplicity of access tracts play a role?
Investigative and clinical urology
Nov 27, 2018
PURPOSE: A prospective study evaluating impact of percutaneous nephrolithotomy (PCNL) on renal function following PCNL using ethylenedicysteine (EC) renal scan. Does multiplicity of access tracts play a role?
SVM-SulfoSite: A support vector machine based predictor for sulfenylation sites.
Scientific reports
Jul 26, 2018
Protein S-sulfenylation, which results from oxidation of free thiols on cysteine residues, has recently emerged as an important post-translational modification that regulates the structure and function of proteins involved in a variety of physiologic...
ApoplastP: prediction of effectors and plant proteins in the apoplast using machine learning.
The New phytologist
Dec 15, 2017
The plant apoplast is integral to intercellular signalling, transport and plant-pathogen interactions. Plant pathogens deliver effectors both into the apoplast and inside host cells, but no computational method currently exists to discriminate betwee...
Protective Effects of Garlic-Derived S-Allylmercaptocysteine on IL-1-Stimulated Chondrocytes by Regulation of MMPs/TIMP-1 Ratio and Type II Collagen Expression via Suppression of NF-B Pathway.
BioMed research international
Dec 3, 2017
BACKGROUND: Garlic-derived S-allylmercaptocysteine (SAMC) has widely been used in many disease therapies. However, the potential effects and mechanism of SAMC on IL-1-stimulated chondrocytes are unclear.
Sequence-Based Prediction of Cysteine Reactivity Using Machine Learning.
Biochemistry
Oct 26, 2017
As one of the most intrinsically reactive amino acids, cysteine carries a variety of important biochemical functions, including catalysis and redox regulation. Discovery and characterization of cysteines with heightened reactivity will help annotate ...
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