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Cysteine

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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
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?

Sequence-Based Prediction of Cysteine Reactivity Using Machine Learning.

Biochemistry
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 ...

ApoplastP: prediction of effectors and plant proteins in the apoplast using machine learning.

The New phytologist
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...

SVM-SulfoSite: A support vector machine based predictor for sulfenylation sites.

Scientific reports
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...

Rapid Identification of Disulfide Bonds and Cysteine-Related Variants in an IgG1 Knob-into-Hole Bispecific Antibody Enhanced by Machine Learning.

Analytical chemistry
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....

Exploring the limitations of biophysical propensity scales coupled with machine learning for protein sequence analysis.

Scientific reports
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...

Prediction of S-nitrosylation sites by integrating support vector machines and random forest.

Molecular omics
Cysteine S-nitrosylation is a type of reversible post-translational modification of proteins, which controls diverse biological processes. It is associated with redox-based cellular signaling to protect against oxidative stress. The identification of...