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  • 1
    Publication Date: 2015-01-16
    Description: Given the increasing number of proteins reported to be regulated by S -nitrosylation (SNO), it is considered to act, in a manner analogous to phosphorylation, as a pleiotropic regulator that elicits dual effects to regulate diverse pathophysiological processes by altering protein function, stability, and conformation change in various cancers and human disorders. Due to its importance in regulating protein functions and cell signaling, dbSNO ( http://dbSNO.mbc.nctu.edu.tw ) is extended as a resource for exploring structural environment of SNO substrate sites and regulatory networks of S -nitrosylated proteins. An increasing interest in the structural environment of PTM substrate sites motivated us to map all manually curated SNO peptides (4165 SNO sites within 2277 proteins) to PDB protein entries by sequence identity, which provides the information of spatial amino acid composition, solvent-accessible surface area, spatially neighboring amino acids, and side chain orientation for 298 substrate cysteine residues. Additionally, the annotations of protein molecular functions, biological processes, functional domains and human diseases are integrated to explore the functional and disease associations for S -nitrosoproteome. In this update, users are allowed to search a group of interested proteins/genes and the system reconstructs the SNO regulatory network based on the information of metabolic pathways and protein-protein interactions. Most importantly, an endogenous yet pathophysiological S -nitrosoproteomic dataset from colorectal cancer patients was adopted to demonstrate that dbSNO could discover potential SNO proteins involving in the regulation of NO signaling for cancer pathways.
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 2
    Publication Date: 2012-06-24
    Description: Motivation: Genome-scale metabolic network models have become an indispensable part of the increasingly important field of systems biology. Metabolic systems biology studies usually include three major components—network model construction, objective- and experiment-guided model editing and visualization, and simulation studies based mainly on flux balance analyses. Bioinformatics tools are required to facilitate these complicated analyses. Although some of the required functions have been served separately by existing tools, a free software resource that simultaneously serves the needs of the three major components is not yet available. Results: Here we present a software platform, GEMSiRV ( GE nome-scale M etabolic model Si mulation, R econstruction and V isualization), to provide functionalities of easy metabolic network drafting and editing, amenable network visualization for experimental data integration and flux balance analysis tools for simulation studies. GEMSiRV comes with downloadable, ready-to-use public-domain metabolic models, reference metabolite/reaction databases and metabolic network maps, all of which can be input into GEMSiRV as the starting materials for network construction or simulation analyses. Furthermore, all of the GEMSiRV-generated metabolic models and analysis results, including projects in progress, can be easily exchanged in the research community. GEMSiRV is a powerful integrative resource that may facilitate the development of systems biology studies. Availability: The software is freely available on the web at http://sb.nhri.org.tw/GEMSiRV . Contact: jade@nhri.org.tw
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
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  • 3
    Publication Date: 2012-05-04
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
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