Summary

A novel software named GPS-SNO 1.0 has been developed to predict specific sites on substrates that undergo S-nitrosylation, providing superior accuracy compared to other existing algorithms. This tool demonstrates an accuracy of 75.80, with a sensitivity of 53.57 and a specificity of 80.14, establishing itself as the most reliable method for identifying these critical molecular targets. The analysis reveals that eukaryotic phospho-regulation is consistently poor at these substrate levels during cell signaling pathways. Furthermore, the findings illustrate a clear structural mismatch between predicted modification sites and actual substrates. Consequently, this software serves as a powerful new methodology capable of analyzing complex in vivo post-translational modification networks that regulate sub-proteomes across different biological systems. The results contribute significantly to our broader understanding of phosphorylation mechanisms and highlight its potential utility for general analysis of the in vivo post-translational modifications regulating sub-proteomes in research contexts.

Title

Ren Lab | Bioinformatics

Description

Ren Lab | Bioinformatics

Keywords

sites, protein, cancer, more, full, abstract, text, read, prediction, modification, variants, proteins, analysis, have, http, data, modifications

NS Lookup

A 162.144.99.67

Dates

Created 2026-04-11

Updated 2026-04-11

Summarized 2026-04-15